Light field displays having synergistic data formatting, re-projection, foveation, tile binning and image warping technology

ABSTRACT

Systems, methods and apparatuses may provide for technology to reduce rendering overhead associated with light field displays. The technology may conduct data formatting, re-projection, foveation, tile binning and/or image warping operations with respect to a plurality of display planes in a light field display.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application is a continuation of and claims the benefit ofpriority to U.S. Non-Provisional patent application Ser. No. 16/723,337filed on Dec. 20, 2019 which is a continuation of and claims the benefitof priority to U.S. Non-Provisional patent application Ser. No.15/858,486 filed Dec. 29, 2017.

COPYRIGHT NOTICE

A portion of the disclosure of this patent document contains materialwhich is subject to (copyright or mask work) protection. The (copyrightor mask work) owner has no objection to the facsimile reproduction byanyone of the patent document or the patent disclosure, as it appears inthe Patent and Trademark Office patent file or records, but otherwisereserves all (copyright or mask work) rights whatsoever.

TECHNICAL FIELD

Embodiments generally relate to graphics systems. More particularly,embodiments relate to light field displays having synergistic dataformatting, re-projection, foveation, tile binning and/or image warpingtechnology.

BACKGROUND OF THE DESCRIPTION

Virtual reality (VR) head mounted display (HMD) technology may use asingle two-dimensional (2D) display plane to present three-dimensional(3D) scenes to the wearer of the HMD. The wearer may experience,however, visual discomfort when attempting to focus on items atdifferent depths in the 3D scene due to a lack of focus cues in thescene. While light field displays may reduce the visual discomfort bycomposing the 3D scene as a light field that is rendered to multipledisplay planes, there remains considerable room for improvement. Forexample, rendering the scene to multiple display planes may increaselatency, reduce performance, increase power consumption and/or reducebattery life.

BRIEF DESCRIPTION OF THE DRAWINGS

The various advantages of the embodiments will become apparent to oneskilled in the art by reading the following specification and appendedclaims, and by referencing the following drawings, in which:

FIG. 1 is a block diagram illustrating a computer system configured toimplement one or more aspects of the embodiments described herein;

FIG. 2A-2D illustrate parallel processor components, according to anembodiment;

FIGS. 3A-3B are block diagrams of graphics multiprocessors, according toembodiments;

FIG. 4A-4F illustrate an exemplary architecture in which a plurality ofGPUs are communicatively coupled to a plurality of multi-coreprocessors;

FIG. 5 illustrates a graphics processing pipeline, according to anembodiment;

FIG. 6A is an illustration of an example of a light field display systemaccording to an embodiment;

FIG. 6B is an illustration of an example of a semiconductor packageapparatus according to an embodiment;

FIG. 6C is an illustration of an example of image data being stored toadjacent memory locations according to an embodiment;

FIG. 6D is a flowchart of an example of a method of managing image datato be rendered across a plurality of display planes according to anembodiment;

FIG. 6E is a flowchart of an example of a method of conducting a memorysetup procedure according to an embodiment;

FIG. 6F is a flowchart of an example of a more detailed method ofmanaging image data to be rendered across a plurality of display planesaccording to an embodiment;

FIG. 7A is an illustration of an example of a source view and are-projected view according to an embodiment;

FIG. 7B is a flowchart of an example of a method of enhancingre-projected views according to an embodiment;

FIG. 7C is a comparative illustration of an example of a non-extendedfield of view and an extended field of view according to an embodiment;

FIG. 7D is a flowchart of an example of a method of filling view holesbased on rasterization data corresponding to a source view according toan embodiment;

FIG. 7E is a flowchart of an example of a method of filling view holesbased on rasterization data corresponding to a re-projected viewaccording to an embodiment;

FIG. 8A is an illustration of an example of a foveated view layoutaccording to an embodiment;

FIG. 8B is a flowchart of an example of a method of foveating scenecontent presented on a plurality of display planes according to anembodiment;

FIG. 8C is an illustration of an example of a peripheral view bin layoutaccording to an embodiment;

FIG. 9A is an illustration of an example of a view frustum tile layoutaccording to an embodiment;

FIG. 9B is an illustration of an example of a light field display viewfrustum layout according to an embodiment;

FIG. 9C is a flowchart of an example of a method of managing primitivesassociated with a plurality of display planes according to anembodiment;

FIG. 9D is an illustration of an example of a near plane-far planedetermination according to an embodiment;

FIG. 9E is an illustration of an example of a coarse frustum cullingdetermination according to an embodiment;

FIGS. 9F and 9G are illustrations of examples of fine frustum cullingdeterminations according to an embodiment;

FIG. 9H is a flowchart of an example of a method of conducting ahierarchical sequence of culling operations according to an embodiment;

FIG. 9I is a flowchart of an example of a more detailed method ofconducting a hierarchical sequence of culling operations according to anembodiment;

FIG. 10A is an illustration of an example of scene content that iswarped across a plurality of display planes according to an embodiment;

FIG. 10B is a flowchart of an example of a method of warping scenecontent across a plurality of display planes according to an embodiment;

FIG. 11 is a block diagram of an example of a display with a localizedbacklight capability according to an embodiment;

FIG. 12A is a block diagram of an example of a data processing deviceaccording to an embodiment;

FIG. 12B is an illustration of an example of a distance determinationaccording to an embodiment;

FIG. 13 is a block diagram of an example of a layered displayarchitecture according to an embodiment;

FIG. 14 is a block diagram of an example of a display architecture thatincludes multiple display units according to an embodiment; and

FIG. 15 is a block diagram of an example of a cloud-assisted mediadelivery architecture according to an embodiment;

FIGS. 16-18 are block diagrams of an example of an overview of a dataprocessing system according to an embodiment;

FIG. 19 is a block diagram of an example of a graphics processing engineaccording to an embodiment;

FIGS. 20-22 are block diagrams of examples of execution units accordingto an embodiment;

FIG. 23 is a block diagram of an example of a graphics pipelineaccording to an embodiment;

FIGS. 24A-24B are block diagrams of examples of graphics pipelineprogramming according to an embodiment;

FIG. 25 is a block diagram of an example of a graphics softwarearchitecture according to an embodiment;

FIG. 26A is a block diagram of an example of an intellectual property(IP) core development system according to an embodiment;

FIG. 26B is a cross-section side view of an example of an integratedcircuit package assembly according to an embodiment;

FIG. 27 is a block diagram of an example of a system on a chipintegrated circuit according to an embodiment;

FIG. 28A is an illustration of an example of a head mounted display(HMD) system according to an embodiment;

FIG. 28B is a block diagram of an example of a graphics processoraccording to an embodiment;

FIGS. 29A-29B are block diagrams examples of graphics processor logicaccording to embodiments; and

FIG. 30 is an illustration of an example of a head mounted display (HMD)system according to an embodiment.

DETAILED DESCRIPTION

In the following description, numerous specific details are set forth toprovide a more thorough understanding of the present invention. However,it will be apparent to one of skill in the art that the presentinvention may be practiced without one or more of these specificdetails. In other instances, well-known features have not been describedin order to avoid obscuring the embodiments.

System Overview

FIG. 1 is a block diagram illustrating a computing system 100 configuredto implement one or more aspects of the embodiments described herein.The computing system 100 includes a processing subsystem 101 having oneor more processor(s) 102 and a system memory 104 communicating via aninterconnection path that may include a memory hub 105. The memory hub105 may be a separate component within a chipset component or may beintegrated within the one or more processor(s) 102. The memory hub 105couples with an I/O subsystem 111 via a communication link 106. The I/Osubsystem 111 includes an I/O hub 107 that can enable the computingsystem 100 to receive input from one or more input device(s) 108.Additionally, the I/O hub 107 can enable a display controller, which maybe included in the one or more processor(s) 102, to provide outputs toone or more display device(s) 110A. In one embodiment the one or moredisplay device(s) 110A coupled with the I/O hub 107 can include a local,internal, or embedded display device.

In one embodiment the processing subsystem 101 includes one or moreparallel processor(s) 112 coupled to memory hub 105 via a bus or othercommunication link 113. The communication link 113 may be one of anynumber of standards based communication link technologies or protocols,such as, but not limited to PCI Express, or may be a vendor specificcommunications interface or communications fabric. In one embodiment theone or more parallel processor(s) 112 form a computationally focusedparallel or vector processing system that an include a large number ofprocessing cores and/or processing clusters, such as a many integratedcore (MIC) processor. In one embodiment the one or more parallelprocessor(s) 112 form a graphics processing subsystem that can outputpixels to one of the one or more display device(s) 110A coupled via theI/O Hub 107. The one or more parallel processor(s) 112 can also includea display controller and display interface (not shown) to enable adirect connection to one or more display device(s) 110B.

Within the I/O subsystem 111, a system storage unit 114 can connect tothe I/O hub 107 to provide a storage mechanism for the computing system100. An I/O switch 116 can be used to provide an interface mechanism toenable connections between the I/O hub 107 and other components, such asa network adapter 118 and/or wireless network adapter 119 that may beintegrated into the platform, and various other devices that can beadded via one or more add-in device(s) 120. The network adapter 118 canbe an Ethernet adapter or another wired network adapter. The wirelessnetwork adapter 119 can include one or more of a Wi-Fi, Bluetooth, nearfield communication (NFC), or other network device that includes one ormore wireless radios.

The computing system 100 can include other components not explicitlyshown, including Universal Serial Bus (USB) or other port connections,optical storage drives, video capture devices, and the like, may also beconnected to the I/O hub 107. Communication paths interconnecting thevarious components in FIG. 1 may be implemented using any suitableprotocols, such as PCI (Peripheral Component Interconnect) basedprotocols (e.g., PCI-Express), or any other bus or point-to-pointcommunication interfaces and/or protocol(s), such as the NV-Linkhigh-speed interconnect, or interconnect protocols known in the art.

In one embodiment, the one or more parallel processor(s) 112 incorporatecircuitry optimized for graphics and video processing, including, forexample, video output circuitry, and constitutes a graphics processingunit (GPU). In another embodiment, the one or more parallel processor(s)112 incorporate circuitry optimized for general purpose processing,while preserving the underlying computational architecture, described ingreater detail herein. In yet another embodiment, components of thecomputing system 100 may be integrated with one or more other systemelements on a single integrated circuit. For example, the one or moreparallel processor(s) 112, memory hub 105, processor(s) 102, and I/O hub107 can be integrated into a system on chip (SoC) integrated circuit.Alternatively, the components of the computing system 100 can beintegrated into a single package to form a system in package (SIP)configuration. In one embodiment at least a portion of the components ofthe computing system 100 can be integrated into a multi-chip module(MCM), which can be interconnected with other multi-chip modules into amodular computing system.

It will be appreciated that the computing system 100 shown herein isillustrative and that variations and modifications are possible. Theconnection topology, including the number and arrangement of bridges,the number of processor(s) 102, and the number of parallel processor(s)112, may be modified as desired. For instance, in some embodiments,system memory 104 is connected to the processor(s) 102 directly ratherthan through a bridge, while other devices communicate with systemmemory 104 via the memory hub 105 and the processor(s) 102. In otheralternative topologies, the parallel processor(s) 112 are connected tothe I/O hub 107 or directly to one of the one or more processor(s) 102,rather than to the memory hub 105. In other embodiments, the I/O hub 107and memory hub 105 may be integrated into a single chip. Someembodiments may include two or more sets of processor(s) 102 attachedvia multiple sockets, which can couple with two or more instances of theparallel processor(s) 112.

Some of the particular components shown herein are optional and may notbe included in all implementations of the computing system 100. Forexample, any number of add-in cards or peripherals may be supported, orsome components may be eliminated. Furthermore, some architectures mayuse different terminology for components similar to those illustrated inFIG. 1. For example, the memory hub 105 may be referred to as aNorthbridge in some architectures, while the I/O hub 107 may be referredto as a Southbridge.

FIG. 2A illustrates a parallel processor 200, according to anembodiment. The various components of the parallel processor 200 may beimplemented using one or more integrated circuit devices, such asprogrammable processors, application specific integrated circuits(ASICs), or field programmable gate arrays (FPGAs). The illustratedparallel processor 200 is a variant of the one or more parallelprocessor(s) 112 shown in FIG. 1, according to an embodiment.

In one embodiment, the parallel processor 200 includes a parallelprocessing unit 202. The parallel processing unit includes an I/O unit204 that enables communication with other devices, including otherinstances of the parallel processing unit 202. The I/O unit 204 may bedirectly connected to other devices. In one embodiment, the I/O unit 204connects with other devices via the use of a hub or switch interface,such as memory hub 105. The connections between the memory hub 105 andthe I/O unit 204 form a communication link 113. Within the parallelprocessing unit 202, the/O unit 204 connects with a host interface 206and a memory crossbar 216, where the host interface 206 receivescommands directed to performing processing operations and the memorycrossbar 216 receives commands directed to performing memory operations.

When the host interface 206 receives a command buffer via the I/O unit204, the host interface 206 can direct work operations to perform thosecommands to a front end 208. In one embodiment, the front end 208couples with a scheduler 210, which is configured to distribute commandsor other work items to a processing cluster array 212. In oneembodiment, the scheduler 210 ensures that the processing cluster array212 is properly configured and in a valid state before tasks aredistributed to the processing clusters of the processing cluster array212. In one embodiment, the scheduler 210 is implemented via firmwarelogic executing on a microcontroller. The microcontroller implementedscheduler 210 is configurable to perform complex scheduling and workdistribution operations at coarse and fine granularity, enabling rapidpreemption and context switching of threads executing on the processingarray 212. In one embodiment, the host software can provide workloadsfor scheduling on the processing array 212 via one of multiple graphicsprocessing doorbells. The workloads can then be automaticallydistributed across the processing array 212 by the scheduler 210 logicwithin the scheduler microcontroller.

The processing cluster array 212 can include up to “N” processingclusters (e.g., cluster 214A, cluster 214B, through cluster 214N). Eachcluster 214A-214N of the processing cluster array 212 can execute alarge number of concurrent threads. The scheduler 210 can allocate workto the clusters 214A-214N of the processing cluster array 212 usingvarious scheduling and/or work distribution algorithms, which may varydepending on the workload arising for each type of program orcomputation. The scheduling can be handled dynamically by the scheduler210, or can be assisted in part by compiler logic during compilation ofprogram logic configured for execution by the processing cluster array212. In one embodiment, different clusters 214A-214N of the processingcluster array 212 can be allocated for processing different types ofprograms or for performing different types of computations.

The processing cluster array 212 can be configured to perform varioustypes of parallel processing operations. In one embodiment, theprocessing cluster array 212 is configured to perform general-purposeparallel compute operations. For example, the processing cluster array212 can include logic to execute processing tasks including filtering ofvideo and/or audio data, performing modeling operations, includingphysics operations, and performing data transformations.

In one embodiment, the processing cluster array 212 is configured toperform parallel graphics processing operations. In embodiments in whichthe parallel processor 200 is configured to perform graphics processingoperations, the processing cluster array 212 can include additionallogic to support the execution of such graphics processing operations,including, but not limited to texture sampling logic to perform textureoperations, as well as tessellation logic and other vertex processinglogic. Additionally, the processing cluster array 212 can be configuredto execute graphics processing related shader programs such as, but notlimited to vertex shaders, tessellation shaders, geometry shaders, andpixel shaders. The parallel processing unit 202 can transfer data fromsystem memory via the I/O unit 204 for processing. During processing,the transferred data can be stored to on-chip memory (e.g., parallelprocessor memory 222), then written back to system memory.

In one embodiment, when the parallel processing unit 202 is used toperform graphics processing, the scheduler 210 can be configured todivide the processing workload into approximately equal sized tasks, tobetter enable distribution of the graphics processing operations tomultiple clusters 214A-214N of the processing cluster array 212. In someembodiments, portions of the processing cluster array 212 can beconfigured to perform different types of processing. For example, afirst portion may be configured to perform vertex shading and topologygeneration, a second portion may be configured to perform tessellationand geometry shading, and a third portion may be configured to performpixel shading or other screen space operations, to produce a renderedimage for display. Intermediate data produced by one or more of theclusters 214A-214N may be stored in buffers to allow the intermediatedata to be transmitted between clusters 214A-214N for furtherprocessing.

During operation, the processing cluster array 212 can receiveprocessing tasks to be executed via the scheduler 210, which receivescommands defining processing tasks from front end 208. For graphicsprocessing operations, processing tasks can include indices of data tobe processed, e.g., surface (patch) data, primitive data, vertex data,and/or pixel data, as well as state parameters and commands defining howthe data is to be processed (e.g., what program is to be executed). Thescheduler 210 may be configured to fetch the indices corresponding tothe tasks or may receive the indices from the front end 208. The frontend 208 can be configured to ensure the processing cluster array 212 isconfigured to a valid state before the workload specified by incomingcommand buffers (e.g., batch-buffers, push buffers, etc.) is initiated.

Each of the one or more instances of the parallel processing unit 202can couple with parallel processor memory 222. The parallel processormemory 222 can be accessed via the memory crossbar 216, which canreceive memory requests from the processing cluster array 212 as well asthe I/O unit 204. The memory crossbar 216 can access the parallelprocessor memory 222 via a memory interface 218. The memory interface218 can include multiple partition units (e.g., partition unit 220A,partition unit 220B, through partition unit 220N) that can each coupleto a portion (e.g., memory unit) of parallel processor memory 222. Inone implementation, the number of partition units 220A-220N isconfigured to be equal to the number of memory units, such that a firstpartition unit 220A has a corresponding first memory unit 224A, a secondpartition unit 220B has a corresponding memory unit 224B, and an Nthpartition unit 220N has a corresponding Nth memory unit 224N. In otherembodiments, the number of partition units 220A-220N may not be equal tothe number of memory devices.

In various embodiments, the memory units 224A-224N can include varioustypes of memory devices, including dynamic random access memory (DRAM)or graphics random access memory, such as synchronous graphics randomaccess memory (SGRAM), including graphics double data rate (GDDR)memory. In one embodiment, the memory units 224A-224N may also include3D stacked memory, including but not limited to high bandwidth memory(HBM). Persons skilled in the art will appreciate that the specificimplementation of the memory units 224A-224N can vary, and can beselected from one of various conventional designs. Render targets, suchas frame buffers or texture maps may be stored across the memory units224A-224N, allowing partition units 220A-220N to write portions of eachrender target in parallel to efficiently use the available bandwidth ofparallel processor memory 222. In some embodiments, a local instance ofthe parallel processor memory 222 may be excluded in favor of a unifiedmemory design that utilizes system memory in conjunction with localcache memory.

In one embodiment, any one of the clusters 214A-214N of the processingcluster array 212 can process data that will be written to any of thememory units 224A-224N within parallel processor memory 222. The memorycrossbar 216 can be configured to transfer the output of each cluster214A-214N to any partition unit 220A-220N or to another cluster214A-214N, which can perform additional processing operations on theoutput. Each cluster 214A-214N can communicate with the memory interface218 through the memory crossbar 216 to read from or write to variousexternal memory devices. In one embodiment, the memory crossbar 216 hasa connection to the memory interface 218 to communicate with the I/Ounit 204, as well as a connection to a local instance of the parallelprocessor memory 222, enabling the processing units within the differentprocessing clusters 214A-214N to communicate with system memory or othermemory that is not local to the parallel processing unit 202. In oneembodiment, the memory crossbar 216 can use virtual channels to separatetraffic streams between the clusters 214A-214N and the partition units220A-220N.

While a single instance of the parallel processing unit 202 isillustrated within the parallel processor 200, any number of instancesof the parallel processing unit 202 can be included. For example,multiple instances of the parallel processing unit 202 can be providedon a single add-in card, or multiple add-in cards can be interconnected.The different instances of the parallel processing unit 202 can beconfigured to inter-operate even if the different instances havedifferent numbers of processing cores, different amounts of localparallel processor memory, and/or other configuration differences. Forexample and in one embodiment, some instances of the parallel processingunit 202 can include higher precision floating point units relative toother instances. Systems incorporating one or more instances of theparallel processing unit 202 or the parallel processor 200 can beimplemented in a variety of configurations and form factors, includingbut not limited to desktop, laptop, or handheld personal computers,servers, workstations, game consoles, and/or embedded systems.

FIG. 2B is a block diagram of a partition unit 220, according to anembodiment. In one embodiment, the partition unit 220 is an instance ofone of the partition units 220A-220N of FIG. 2A. As illustrated, thepartition unit 220 includes an L2 cache 221, a frame buffer interface225, and a ROP 226 (raster operations unit). The L2 cache 221 is aread/write cache that is configured to perform load and store operationsreceived from the memory crossbar 216 and ROP 226. Read misses andurgent write-back requests are output by L2 cache 221 to frame bufferinterface 225 for processing. Updates can also be sent to the framebuffer via the frame buffer interface 225 for processing. In oneembodiment, the frame buffer interface 225 interfaces with one of thememory units in parallel processor memory, such as the memory units224A-224N of FIG. 2 (e.g., within parallel processor memory 222).

In graphics applications, the ROP 226 is a processing unit that performsraster operations such as stencil, z test, blending, and the like. TheROP 226 then outputs processed graphics data that is stored in graphicsmemory. In some embodiments the ROP 226 includes compression logic tocompress depth or color data that is written to memory and decompressdepth or color data that is read from memory. The compression logic canbe lossless compression logic that makes use of one or more of multiplecompression algorithms. The type of compression that is performed by theROP 226 can vary based on the statistical characteristics of the data tobe compressed. For example, in one embodiment, delta color compressionis performed on depth and color data on a per-tile basis.

In some embodiments, the ROP 226 is included within each processingcluster (e.g., cluster 214A-214N of FIG. 2) instead of within thepartition unit 220. In such embodiment, read and write requests forpixel data are transmitted over the memory crossbar 216 instead of pixelfragment data. The processed graphics data may be displayed on a displaydevice, such as one of the one or more display device(s) 110 of FIG. 1,routed for further processing by the processor(s) 102, or routed forfurther processing by one of the processing entities within the parallelprocessor 200 of FIG. 2A.

FIG. 2C is a block diagram of a processing cluster 214 within a parallelprocessing unit, according to an embodiment. In one embodiment, theprocessing cluster is an instance of one of the processing clusters214A-214N of FIG. 2. The processing cluster 214 can be configured toexecute many threads in parallel, where the term “thread” refers to aninstance of a particular program executing on a particular set of inputdata. In some embodiments, single-instruction, multiple-data (SIMD)instruction issue techniques are used to support parallel execution of alarge number of threads without providing multiple independentinstruction units. In other embodiments, single-instruction,multiple-thread (SIMT) techniques are used to support parallel executionof a large number of generally synchronized threads, using a commoninstruction unit configured to issue instructions to a set of processingengines within each one of the processing clusters. Unlike a SIMDexecution regime, where all processing engines typically executeidentical instructions, SIMT execution allows different threads to morereadily follow divergent execution paths through a given thread program.Persons skilled in the art will understand that a SIMD processing regimerepresents a functional subset of a SIMT processing regime.

Operation of the processing cluster 214 can be controlled via a pipelinemanager 232 that distributes processing tasks to SIMT parallelprocessors. The pipeline manager 232 receives instructions from thescheduler 210 of FIG. 2A and manages execution of those instructions viaa graphics multiprocessor 234 and/or a texture unit 236. The illustratedgraphics multiprocessor 234 is an exemplary instance of a SIMT parallelprocessor. However, various types of SIMT parallel processors ofdiffering architectures may be included within the processing cluster214. One or more instances of the graphics multiprocessor 234 can beincluded within a processing cluster 214. The graphics multiprocessor234 can process data and a data crossbar 240 can be used to distributethe processed data to one of multiple possible destinations, includingother shader units. The pipeline manager 232 can facilitate thedistribution of processed data by specifying destinations for processeddata to be distributed via the data crossbar 240.

Each graphics multiprocessor 234 within the processing cluster 214 caninclude an identical set of functional execution logic (e.g., arithmeticlogic units, load-store units, etc.). The functional execution logic canbe configured in a pipelined manner in which new instructions can beissued before previous instructions are complete. The functionalexecution logic supports a variety of operations including integer andfloating point arithmetic, comparison operations, Boolean operations,bit-shifting, and computation of various algebraic functions. In oneembodiment, the same functional-unit hardware can be leveraged toperform different operations and any combination of functional units maybe present.

The instructions transmitted to the processing cluster 214 constitutes athread. A set of threads executing across the set of parallel processingengines is a thread group. A thread group executes the same program ondifferent input data. Each thread within a thread group can be assignedto a different processing engine within a graphics multiprocessor 234. Athread group may include fewer threads than the number of processingengines within the graphics multiprocessor 234. When a thread groupincludes fewer threads than the number of processing engines, one ormore of the processing engines may be idle during cycles in which thatthread group is being processed. A thread group may also include morethreads than the number of processing engines within the graphicsmultiprocessor 234. When the thread group includes more threads than thenumber of processing engines within the graphics multiprocessor 234,processing can be performed over consecutive clock cycles. In oneembodiment, multiple thread groups can be executed concurrently on agraphics multiprocessor 234.

In one embodiment, the graphics multiprocessor 234 includes an internalcache memory to perform load and store operations. In one embodiment,the graphics multiprocessor 234 can forego an internal cache and use acache memory (e.g., L1 cache 248) within the processing cluster 214.Each graphics multiprocessor 234 also has access to L2 caches within thepartition units (e.g., partition units 220A-220N of FIG. 2) that areshared among all processing clusters 214 and may be used to transferdata between threads. The graphics multiprocessor 234 may also accessoff-chip global memory, which can include one or more of local parallelprocessor memory and/or system memory. Any memory external to theparallel processing unit 202 may be used as global memory. Embodimentsin which the processing cluster 214 includes multiple instances of thegraphics multiprocessor 234 can share common instructions and data,which may be stored in the L1 cache 248.

Each processing cluster 214 may include an MMU 245 (memory managementunit) that is configured to map virtual addresses into physicaladdresses. In other embodiments, one or more instances of the MMU 245may reside within the memory interface 218 of FIG. 2A. The MMU 245includes a set of page table entries (PTEs) used to map a virtualaddress to a physical address of a tile (talk more about tiling) andoptionally a cache line index. The MMU 245 may include addresstranslation lookaside buffers (TLB) or caches that may reside within thegraphics multiprocessor 234 or the L1 cache 248 or processing cluster214. The physical address is processed to distribute surface data accesslocality to allow efficient request interleaving among partition units.The cache line index may be used to determine whether a request for acache line is a hit or miss.

In graphics and computing applications, a processing cluster 214 may beconfigured such that each graphics multiprocessor 234 is coupled to atexture unit 236 for performing texture mapping operations, e.g.,determining texture sample positions, reading texture data, andfiltering the texture data. Texture data is read from an internaltexture L1 cache (not shown) or in some embodiments from the L1 cachewithin graphics multiprocessor 234 and is fetched from an L2 cache,local parallel processor memory, or system memory, as needed. Eachgraphics multiprocessor 234 outputs processed tasks to the data crossbar240 to provide the processed task to another processing cluster 214 forfurther processing or to store the processed task in an L2 cache, localparallel processor memory, or system memory via the memory crossbar 216.A preROP 242 (pre-raster operations unit) is configured to receive datafrom graphics multiprocessor 234, direct data to ROP units, which may belocated with partition units as described herein (e.g., partition units220A-220N of FIG. 2). The preROP 242 unit can perform optimizations forcolor blending, organize pixel color data, and perform addresstranslations.

It will be appreciated that the core architecture described herein isillustrative and that variations and modifications are possible. Anynumber of processing units, e.g., graphics multiprocessor 234, textureunits 236, preROPs 242, etc., may be included within a processingcluster 214. Further, while only one processing cluster 214 is shown, aparallel processing unit as described herein may include any number ofinstances of the processing cluster 214. In one embodiment, eachprocessing cluster 214 can be configured to operate independently ofother processing clusters 214 using separate and distinct processingunits, L1 caches, etc.

FIG. 2D shows a graphics multiprocessor 234, according to oneembodiment. In such embodiment the graphics multiprocessor 234 coupleswith the pipeline manager 232 of the processing cluster 214. Thegraphics multiprocessor 234 has an execution pipeline including but notlimited to an instruction cache 252, an instruction unit 254, an addressmapping unit 256, a register file 258, one or more general purposegraphics processing unit (GPGPU) cores 262, and one or more load/storeunits 266. The GPGPU cores 262 and load/store units 266 are coupled withcache memory 272 and shared memory 270 via a memory and cacheinterconnect 268.

In one embodiment, the instruction cache 252 receives a stream ofinstructions to execute from the pipeline manager 232. The instructionsare cached in the instruction cache 252 and dispatched for execution bythe instruction unit 254. The instruction unit 254 can dispatchinstructions as thread groups (e.g., warps), with each thread of thethread group assigned to a different execution unit within GPGPU core262. An instruction can access any of a local, shared, or global addressspace by specifying an address within a unified address space. Theaddress mapping unit 256 can be used to translate addresses in theunified address space into a distinct memory address that can beaccessed by the load/store units 266.

The register file 258 provides a set of registers for the functionalunits of the graphics multiprocessor 324. The register file 258 providestemporary storage for operands connected to the data paths of thefunctional units (e.g., GPGPU cores 262, load/store units 266) of thegraphics multiprocessor 324. In one embodiment, the register file 258 isdivided between each of the functional units such that each functionalunit is allocated a dedicated portion of the register file 258. In oneembodiment, the register file 258 is divided between the different warpsbeing executed by the graphics multiprocessor 324.

The GPGPU cores 262 can each include floating point units (FPUs) and/orinteger arithmetic logic units (ALUs) that are used to executeinstructions of the graphics multiprocessor 324. The GPGPU cores 262 canbe similar in architecture or can differ in architecture, according toembodiments. For example and in one embodiment, a first portion of theGPGPU cores 262 include a single precision FPU and an integer ALU whilea second portion of the GPGPU cores include a double precision FPU. Inone embodiment, the FPUs can implement the IEEE 754-2008 standard forfloating point arithmetic or enable variable precision floating pointarithmetic. The graphics multiprocessor 234 can additionally include oneor more fixed function or special function units to perform specificfunctions such as copy rectangle or pixel blending operations. In oneembodiment, one or more of the GPGPU cores can also include fixed orspecial function logic.

In one embodiment, the GPGPU cores 262 include SIMD logic capable ofperforming a single instruction on multiple sets of data. In oneembodiment, GPGPU cores 262 can physically execute SIMD4, SIMD8, andSIMD16 instructions and logically execute SIMD1, SIMD2, and SIMD32instructions. The SIMD instructions for the GPGPU cores can be generatedat compile time by a shader compiler or automatically generated whenexecuting programs written and compiled for single program multiple data(SPMD) or SIMT architectures. Multiple threads of a program configuredfor the SIMT execution model can be executed via a single SIMDinstruction. For example and in one embodiment, eight SIMT threads thatperform the same or similar operations can be executed in parallel via asingle SIMD8 logic unit.

The memory and cache interconnect 268 is an interconnect network thatconnects each of the functional units of the graphics multiprocessor 234to the register file 258 and to the shared memory 270. In oneembodiment, the memory and cache interconnect 268 is a crossbarinterconnect that allows the load/store unit 266 to implement load andstore operations between the shared memory 270 and the register file258. The register file 258 can operate at the same frequency as theGPGPU cores 262, thus data transfer between the GPGPU cores 262 and theregister file 258 is very low latency. The shared memory 270 can be usedto enable communication between threads that execute on the functionalunits within the graphics multiprocessor 234. The cache memory 272 canbe used as a data cache for example, to cache texture data communicatedbetween the functional units and the texture unit 236. The shared memory270 can also be used as a program managed cache. Threads executing onthe GPGPU cores 262 can programmatically store data within the sharedmemory in addition to the automatically cached data that is storedwithin the cache memory 272.

FIGS. 3A-3B illustrate additional graphics multiprocessors, according toembodiments. The illustrated graphics multiprocessors 325, 350 arevariants of the graphics multiprocessor 234 of FIG. 2C. The illustratedgraphics multiprocessors 325, 350 can be configured as a streamingmultiprocessor (SM) capable of simultaneous execution of a large numberof execution threads.

FIG. 3A shows a graphics multiprocessor 325 according to an additionalembodiment. The graphics multiprocessor 325 includes multiple additionalinstances of execution resource units relative to the graphicsmultiprocessor 234 of FIG. 2D. For example, the graphics multiprocessor325 can include multiple instances of the instruction unit 332A-332B,register file 334A-334B, and texture unit(s) 344A-344B. The graphicsmultiprocessor 325 also includes multiple sets of graphics or computeexecution units (e.g., GPGPU core 336A-336B, GPGPU core 337A-337B, GPGPUcore 338A-338B) and multiple sets of load/store units 340A-340B. In oneembodiment, the execution resource units have a common instruction cache330, texture and/or data cache memory 342, and shared memory 346.

The various components can communicate via an interconnect fabric 327.In one embodiment, the interconnect fabric 327 includes one or morecrossbar switches to enable communication between the various componentsof the graphics multiprocessor 325. In one embodiment, the interconnectfabric 327 is a separate, high-speed network fabric layer upon whicheach component of the graphics multiprocessor 325 is stacked. Thecomponents of the graphics multiprocessor 325 communicate with remotecomponents via the interconnect fabric 327. For example, the GPGPU cores336A-336B, 337A-337B, and 3378A-338B can each communicate with sharedmemory 346 via the interconnect fabric 327. The interconnect fabric 327can arbitrate communication within the graphics multiprocessor 325 toensure a fair bandwidth allocation between components.

FIG. 3B shows a graphics multiprocessor 350 according to an additionalembodiment. The graphics processor includes multiple sets of executionresources 356A-356D, where each set of execution resource includesmultiple instruction units, register files, GPGPU cores, and load storeunits, as illustrated in FIG. 2D and FIG. 3A. The execution resources356A-356D can work in concert with texture unit(s) 360A-360D for textureoperations, while sharing an instruction cache 354, and shared memory362. In one embodiment, the execution resources 356A-356D can share aninstruction cache 354 and shared memory 362, as well as multipleinstances of a texture and/or data cache memory 358A-358B. The variouscomponents can communicate via an interconnect fabric 352 similar to theinterconnect fabric 327 of FIG. 3A.

Persons skilled in the art will understand that the architecturedescribed in FIGS. 1, 2A-2D, and 3A-3B are descriptive and not limitingas to the scope of the present embodiments. Thus, the techniquesdescribed herein may be implemented on any properly configuredprocessing unit, including, without limitation, one or more mobileapplication processors, one or more desktop or server central processingunits (CPUs) including multi-core CPUs, one or more parallel processingunits, such as the parallel processing unit 202 of FIG. 2A, as well asone or more graphics processors or special purpose processing units,without departure from the scope of the embodiments described herein.

In some embodiments, a parallel processor or GPGPU as described hereinis communicatively coupled to host/processor cores to accelerategraphics operations, machine-learning operations, pattern analysisoperations, and various general purpose GPU (GPGPU) functions. The GPUmay be communicatively coupled to the host processor/cores over a bus orother interconnect (e.g., a high speed interconnect such as PCIe orNVLink). In other embodiments, the GPU may be integrated on the samepackage or chip as the cores and communicatively coupled to the coresover an internal processor bus/interconnect (i.e., internal to thepackage or chip). Regardless of the manner in which the GPU isconnected, the processor cores may allocate work to the GPU in the formof sequences of commands/instructions contained in a work descriptor.The GPU then uses dedicated circuitry/logic for efficiently processingthese commands/instructions.

Techniques for GPU to Host Processor Interconnection

FIG. 4A illustrates an exemplary architecture in which a plurality ofGPUs 410-413 are communicatively coupled to a plurality of multi-coreprocessors 405-406 over high-speed links 440-443 (e.g., buses,point-to-point interconnects, etc.). In one embodiment, the high-speedlinks 440-443 support a communication throughput of 4 GB/s, 30 GB/s, 80GB/s or higher, depending on the implementation. Various interconnectprotocols may be used including, but not limited to, PCIe 4.0 or 5.0 andNVLink 2.0. However, the underlying principles of the invention are notlimited to any particular communication protocol or throughput.

In addition, in one embodiment, two or more of the GPUs 410-413 areinterconnected over high-speed links 444-445, which may be implementedusing the same or different protocols/links than those used forhigh-speed links 440-443. Similarly, two or more of the multi-coreprocessors 405-406 may be connected over high speed link 433 which maybe symmetric multi-processor (SMP) buses operating at 20 GB/s, 30 GB/s,120 GB/s or higher. Alternatively, all communication between the varioussystem components shown in FIG. 4A may be accomplished using the sameprotocols/links (e.g., over a common interconnection fabric). Asmentioned, however, the underlying principles of the invention are notlimited to any particular type of interconnect technology.

In one embodiment, each multi-core processor 405-406 is communicativelycoupled to a processor memory 401-402, via memory interconnects 430-431,respectively, and each GPU 410-413 is communicatively coupled to GPUmemory 420-423 over GPU memory interconnects 450-453, respectively. Thememory interconnects 430-431 and 450-453 may utilize the same ordifferent memory access technologies. By way of example, and notlimitation, the processor memories 401-402 and GPU memories 420-423 maybe volatile memories such as dynamic random access memories (DRAMs)(including stacked DRAMs), Graphics DDR SDRAM (GDDR) (e.g., GDDR5,GDDR6), or High Bandwidth Memory (HBM) and/or may be non-volatilememories such as 3D XPoint or Nano-Ram. In one embodiment, some portionof the memories may be volatile memory and another portion may benon-volatile memory (e.g., using a two-level memory (2LM) hierarchy).

As described below, although the various processors 405-406 and GPUs410-413 may be physically coupled to a particular memory 401-402,420-423, respectively, a unified memory architecture may be implementedin which the same virtual system address space (also referred to as the“effective address” space) is distributed among all of the variousphysical memories. For example, processor memories 401-402 may eachcomprise 64 GB of the system memory address space and GPU memories420-423 may each comprise 32 GB of the system memory address space(resulting in a total of 256 GB addressable memory in this example).

FIG. 4B illustrates additional details for an interconnection between amulti-core processor 407 and a graphics acceleration module 446 inaccordance with one embodiment. The graphics acceleration module 446 mayinclude one or more GPU chips integrated on a line card which is coupledto the processor 407 via the high-speed link 440. Alternatively, thegraphics acceleration module 446 may be integrated on the same packageor chip as the processor 407.

The illustrated processor 407 includes a plurality of cores 460A-460D,each with a translation lookaside buffer 461A-461D and one or morecaches 462A-462D. The cores may include various other components forexecuting instructions and processing data which are not illustrated toavoid obscuring the underlying principles of the invention (e.g.,instruction fetch units, branch prediction units, decoders, executionunits, reorder buffers, etc.). The caches 462A-462D may comprise level 1(L1) and level 2 (L2) caches. In addition, one or more shared caches 456may be included in the caching hierarchy and shared by sets of the cores460A-460D. For example, one embodiment of the processor 407 includes 24cores, each with its own L1 cache, twelve shared L2 caches, and twelveshared L3 caches. In this embodiment, one of the L2 and L3 caches areshared by two adjacent cores. The processor 407 and the graphicsaccelerator integration module 446 connect with system memory 441, whichmay include processor memories 401-402.

Coherency is maintained for data and instructions stored in the variouscaches 462A-462D, 456 and system memory 441 via inter-core communicationover a coherence bus 464. For example, each cache may have cachecoherency logic/circuitry associated therewith to communicate to overthe coherence bus 464 in response to detected reads or writes toparticular cache lines. In one implementation, a cache snooping protocolis implemented over the coherence bus 464 to snoop cache accesses. Cachesnooping/coherency techniques are well understood by those of skill inthe art and will not be described in detail here to avoid obscuring theunderlying principles of the invention.

In one embodiment, a proxy circuit 425 communicatively couples thegraphics acceleration module 446 to the coherence bus 464, allowing thegraphics acceleration module 446 to participate in the cache coherenceprotocol as a peer of the cores. In particular, an interface 435provides connectivity to the proxy circuit 425 over high-speed link 440(e.g., a PCIe bus, NVLink, etc.) and an interface 437 connects thegraphics acceleration module 446 to the link 440.

In one implementation, an accelerator integration circuit 436 providescache management, memory access, context management, and interruptmanagement services on behalf of a plurality of graphics processingengines 431, 432N, of the graphics acceleration module 446. The graphicsprocessing engines 431, 432N, may each comprise a separate graphicsprocessing unit (GPU). Alternatively, the graphics processing engines431,432N, may comprise different types of graphics processing engineswithin a GPU such as graphics execution units, media processing engines(e.g., video encoders/decoders), samplers, and blit engines. In otherwords, the graphics acceleration module may be a GPU with a plurality ofgraphics processing engines 431-432N, or the graphics processing engines431-432N, may be individual GPUs integrated on a common package, linecard, or chip.

In one embodiment, the accelerator integration circuit 436 includes amemory management unit (MMU) 439 for performing various memorymanagement functions such as virtual-to-physical memory translations(also referred to as effective-to-real memory translations) and memoryaccess protocols for accessing system memory 441. The MMU 439 may alsoinclude a translation lookaside buffer (TLB) (not shown) for caching thevirtual/effective to physical/real address translations. In oneimplementation, a cache 438 stores commands and data for efficientaccess by the graphics processing engines 431-432N. In one embodiment,the data stored in cache 438 and graphics memories 433-434N, is keptcoherent with the core caches 462A-462D, 456 and system memory 411. Asmentioned, this may be accomplished via proxy circuit 425, which takespart in the cache coherency mechanism on behalf of cache 438 andmemories 433-434N, (e.g., sending updates to the cache 438 related tomodifications/accesses of cache lines on processor caches 462A-462D, 456and receiving updates from the cache 438).

A set of registers 445 store context data for threads executed by thegraphics processing engines 431-432N, and a context management circuit448 manages the thread contexts. For example, the context managementcircuit 448 may perform save and restore operations to save and restorecontexts of the various threads during contexts switches (e.g., where afirst thread is saved and a second thread is stored so that the secondthread can be execute by a graphics processing engine). For example, ona context switch, the context management circuit 448 may store currentregister values to a designated region in memory (e.g., identified by acontext pointer). It may then restore the register values when returningto the context. In one embodiment, an interrupt management circuit 447receives and processes interrupts received from system devices.

In one implementation, virtual/effective addresses from a graphicsprocessing engine 431 are translated to real/physical addresses insystem memory 411 by the MMU 439. One embodiment of the acceleratorintegration circuit 436 supports multiple (e.g., 4, 8, 16) graphicsaccelerator modules 446 and/or other accelerator devices. The graphicsaccelerator module 446 may be dedicated to a single application executedon the processor 407 or may be shared between multiple applications. Inone embodiment, a virtualized graphics execution environment ispresented in which the resources of the graphics processing engines431-432N, are shared with multiple applications or virtual machines(VMs). The resources may be subdivided into “slices”, which areallocated to different VMs and/or applications based on the processingrequirements and priorities associated with the VMs and/or applications.

Thus, the accelerator integration circuit acts as a bridge to the systemfor the graphics acceleration module 446 and provides addresstranslation and system memory cache services. In addition, theaccelerator integration circuit 436 may provide virtualizationfacilities for the host processor to manage virtualization of thegraphics processing engines, interrupts, and memory management.

Because hardware resources of the graphics processing engines 431-432N,are mapped explicitly to the real address space seen by the hostprocessor 407, any host processor can address these resources directlyusing an effective address value. One function of the acceleratorintegration circuit 436, in one embodiment, is the physical separationof the graphics processing engines 431-432N, so that they appear to thesystem as independent units.

As mentioned, in the illustrated embodiment, one or more graphicsmemories 433-434M, are coupled to each of the graphics processingengines 431-432N, respectively. The graphics memories 433-434M, storeinstructions and data being processed by each of the graphics processingengines 431-432N. The graphics memories 433-434M, may be volatilememories such as DRAMs (including stacked DRAMs), GDDR memory (e.g.,GDDR5, GDDR6), or HBM, and/or may be non-volatile memories such as 3DXPoint or Nano-Ram.

In one embodiment, to reduce data traffic over link 440, biasingtechniques are used to ensure that the data stored in graphics memories433-434M, is data which will be used most frequently by the graphicsprocessing engines 431-432N, and preferably not used by the cores460A-460D (at least not frequently). Similarly, the biasing mechanismattempts to keep data needed by the cores (and preferably not thegraphics processing engines 431-432N,) within the caches 462A-462D, 456of the cores and system memory 411.

FIG. 4C illustrates another embodiment in which the acceleratorintegration circuit 436 is integrated within the processor 407. In thisembodiment, the graphics processing engines 431-432N, communicatedirectly over the high-speed link 440 to the accelerator integrationcircuit 436 via interface 437 and interface 435 (which, again, may beutilize any form of bus or interface protocol). The acceleratorintegration circuit 436 may perform the same operations as thosedescribed with respect to FIG. 4B, but potentially at a higherthroughput given its close proximity to the coherency bus 462 and caches462A-462D, 426.

One embodiment supports different programming models including adedicated-process programming model (no graphics acceleration modulevirtualization) and shared programming models (with virtualization). Thelatter may include programming models which are controlled by theaccelerator integration circuit 436 and programming models which arecontrolled by the graphics acceleration module 446.

In one embodiment of the dedicated process model, graphics processingengines 431-432N, are dedicated to a single application or process undera single operating system. The single application can funnel otherapplication requests to the graphics engines 431-432N, providingvirtualization within a virtual machine (VM)/partition.

In the dedicated-process programming models, the graphics processingengines 431-432N, may be shared by multiple VM/application partitions.The shared models require a system hypervisor to virtualize the graphicsprocessing engines 431-432N, to allow access by each operating system.For single-partition systems without a hypervisor, the graphicsprocessing engines 431-432N, are owned by the operating system. In bothcases, the operating system can virtualize the graphics processingengines 431-432N, to provide access to each process or application.

For the shared programming model, the graphics acceleration module 446or an individual graphics processing engine 431-432N, selects a processelement using a process handle. In one embodiment, process elements arestored in system memory and are addressable using the effective addressto real address translation techniques described herein. The processhandle may be an implementation-specific value provided to the hostprocess when registering its context with the graphics processing engine431-432N, (that is, calling system software to add the process elementto the process element linked list). The lower 16-bits of the processhandle may be the offset of the process element within the processelement linked list.

FIG. 4D illustrates an exemplary accelerator integration slice 490. Asused herein, a “slice” comprises a specified portion of the processingresources of the accelerator integration circuit 436. Applicationeffective address space 482 within system memory 411 stores processelements 483. In one embodiment, the process elements 483 are stored inresponse to GPU invocations 481 from applications 480 executed on theprocessor 407. A process element 483 contains the process state for thecorresponding application 480. A work descriptor (WD) 484 contained inthe process element 483 can be a single job requested by an applicationor may contain a pointer to a queue of jobs. In the latter case, the WD484 is a pointer to the job request queue in the application's addressspace 482.

The graphics acceleration module 446 and/or the individual graphicsprocessing engines 431-432N, can be shared by all or a subset of theprocesses in the system. Embodiments of the invention include aninfrastructure for setting up the process state and sending a WD 484 toa graphics acceleration module 446 to start a job in a virtualizedenvironment.

In one implementation, the dedicated-process programming model isimplementation-specific. In this model, a single process owns thegraphics acceleration module 446 or an individual graphics processingengine 431. Because the graphics acceleration module 446 is owned by asingle process, the hypervisor initializes the accelerator integrationcircuit 436 for the owning partition and the operating systeminitializes the accelerator integration circuit 436 for the owningprocess at the time when the graphics acceleration module 446 isassigned.

In operation, a WD fetch unit 491 in the accelerator integration slice490 fetches the next WD 484, which includes an indication of the work tobe done by one of the graphics processing engines of the graphicsacceleration module 446. Data from the WD 484 may be stored in registers445 and used by the MMU 439, interrupt management circuit 447 and/orcontext management circuit 448 as illustrated. For example, oneembodiment of the MMU 439 includes segment/page walk circuitry foraccessing segment/page tables 486 within the OS virtual address space485. The interrupt management circuit 447 may process interrupt events492 received from the graphics acceleration module 446. When performinggraphics operations, an effective address 493 generated by a graphicsprocessing engine 431-432N, is translated to a real address by the MMU439.

In one embodiment, the same set of registers 445 are duplicated for eachgraphics processing engine 431-432N, and/or graphics acceleration module446 and may be initialized by the hypervisor or operating system. Eachof these duplicated registers may be included in an acceleratorintegration slice 490. Exemplary registers that may be initialized bythe hypervisor are shown in Table 1.

TABLE 1 Hypervisor Initialized Registers 1 Slice Control Register 2 RealAddress (RA) Scheduled Processes Area Pointer 3 Authority Mask OverrideRegister 4 Interrupt Vector Table Entry Offset 5 Interrupt Vector TableEntry Limit 6 State Register 7 Logical Partition ID 8 Real address (RA)Hypervisor Accelerator Utilization Record Pointer 9 Storage DescriptionRegister

Exemplary registers that may be initialized by the operating system areshown in Table 2.

TABLE 2 Operating System Initialized Registers 1 Process and ThreadIdentification 2 Effective Address (EA) Context Save/Restore Pointer 3Virtual Address (VA) Accelerator Utilization Record Pointer 4 VirtualAddress (VA) Storage Segment Table Pointer 5 Authority Mask 6 Workdescriptor

In one embodiment, each WD 484 is specific to a particular graphicsacceleration module 446 and/or graphics processing engine 431-432N. Itcontains all the information a graphics processing engine 431-432N,requires to do its work or it can be a pointer to a memory locationwhere the application has set up a command queue of work to becompleted.

FIG. 4E illustrates additional details for one embodiment of a sharedmodel. This embodiment includes a hypervisor real address space 498 inwhich a process element list 499 is stored. The hypervisor real addressspace 498 is accessible via a hypervisor 496, which virtualizes thegraphics acceleration module engines for the operating system 495.

The shared programming models allow for all or a subset of processesfrom all or a subset of partitions in the system to use a graphicsacceleration module 446. There are two programming models where thegraphics acceleration module 446 is shared by multiple processes andpartitions: time-sliced shared and graphics directed shared.

In this model, the system hypervisor 496 owns the graphics accelerationmodule 446 and makes its function available to all operating systems495. For a graphics acceleration module 446 to support virtualization bythe system hypervisor 496, the graphics acceleration module 446 mayadhere to the following requirements: 1) An application's job requestmust be autonomous (that is, the state does not need to be maintainedbetween jobs), or the graphics acceleration module 446 must provide acontext save and restore mechanism. 2) An application's job request isguaranteed by the graphics acceleration module 446 to complete in aspecified amount of time, including any translation faults, or thegraphics acceleration module 446 provides the ability to preempt theprocessing of the job. 3) The graphics acceleration module 446 must beguaranteed fairness between processes when operating in the directedshared programming model.

In one embodiment, for the shared model, the application 480 is requiredto make an operating system 495 system call with a graphics accelerationmodule 446 type, a work descriptor (WD), an authority mask register(AMR) value, and a context save/restore area pointer (CSRP). Thegraphics acceleration module 446 type describes the targetedacceleration function for the system call. The graphics accelerationmodule 446 type may be a system-specific value. The WD is formattedspecifically for the graphics acceleration module 446 and can be in theform of a graphics acceleration module 446 command, an effective addresspointer to a user-defined structure, an effective address pointer to aqueue of commands, or any other data structure to describe the work tobe done by the graphics acceleration module 446. In one embodiment, theAMR value is the AMR state to use for the current process. The valuepassed to the operating system is similar to an application setting theAMR. If the accelerator integration circuit 436 and graphicsacceleration module 446 implementations do not support a User AuthorityMask Override Register (UAMOR), the operating system may apply thecurrent UAMOR value to the AMR value before passing the AMR in thehypervisor call. The hypervisor 496 may optionally apply the currentAuthority Mask Override Register (AMOR) value before placing the AMRinto the process element 483. In one embodiment, the CSRP is one of theregisters 445 containing the effective address of an area in theapplication's address space 482 for the graphics acceleration module 446to save and restore the context state. This pointer is optional if nostate is required to be saved between jobs or when a job is preempted.The context save/restore area may be pinned system memory.

Upon receiving the system call, the operating system 495 may verify thatthe application 480 has registered and been given the authority to usethe graphics acceleration module 446. The operating system 495 thencalls the hypervisor 496 with the information shown in Table 3.

TABLE 3 OS to Hypervisor Call Parameters 1 A work descriptor (WD) 2 AnAuthority Mask Register (AMR) value (potentially masked). 3 An effectiveaddress (EA) Context Save/Restore Area Pointer (CSRP) 4 A process ID(ND) and optional thread ID (TID) 5 A virtual address (VA) acceleratorutilization record pointer (AURP) 6 The virtual address of the storagesegment table pointer (SSTP) 7 A logical interrupt service number (LISN)

Upon receiving the hypervisor call, the hypervisor 496 verifies that theoperating system 495 has registered and been given the authority to usethe graphics acceleration module 446. The hypervisor 496 then puts theprocess element 483 into the process element linked list for thecorresponding graphics acceleration module 446 type. The process elementmay include the information shown in Table 4.

TABLE 4 Process Element Information  1 A work descriptor (WD)  2 AnAuthority Mask Register (AMR) value (potentially masked).  3 Aneffective address (EA) Context Save/Restore Area Pointer (CSRP)  4 Aprocess ID (PID) and optional thread ID (TID)  5 A virtual address (VA)accelerator utilization record pointer (AURP)  6 The virtual address ofthe storage segment table pointer (SSTP)  7 A logical interrupt servicenumber (LISN)  8 Interrupt vector table, derived from the hypervisorcall parameters.  9 A state register (SR) value 10 A logical partitionID (LPID) 11 A real address (RA) hypervisor accelerator utilizationrecord pointer 12 The Storage Descriptor Register (SDR)

In one embodiment, the hypervisor initializes a plurality of acceleratorintegration slice 490 registers 445.

As illustrated in FIG. 4F, one embodiment of the invention employs aunified memory addressable via a common virtual memory address spaceused to access the physical processor memories 401-402 and GPU memories420-423. In this implementation, operations executed on the GPUs 410-413utilize the same virtual/effective memory address space to access theprocessors memories 401-402 and vice versa, thereby simplifyingprogrammability. In one embodiment, a first portion of thevirtual/effective address space is allocated to the processor memory401, a second portion to the second processor memory 402, a thirdportion to the GPU memory 420, and so on. The entire virtual/effectivememory space (sometimes referred to as the effective address space) isthereby distributed across each of the processor memories 401-402 andGPU memories 420-423, allowing any processor or GPU to access anyphysical memory with a virtual address mapped to that memory.

In one embodiment, bias/coherence management circuitry 494A-494E withinone or more of the MMUs 439A-439E ensures cache coherence between thecaches of the host processors (e.g., 405) and the GPUs 410-413 andimplements biasing techniques indicating the physical memories in whichcertain types of data should be stored. While multiple instances ofbias/coherence management circuitry 494A-494E are illustrated in FIG.4F, the bias/coherence circuitry may be implemented within the MMU ofone or more host processors 405 and/or within the acceleratorintegration circuit 436.

One embodiment allows GPU-attached memory 420-423 to be mapped as partof system memory, and accessed using shared virtual memory (SVM)technology, but without suffering the typical performance drawbacksassociated with full system cache coherence. The ability to GPU-attachedmemory 420-423 to be accessed as system memory without onerous cachecoherence overhead provides a beneficial operating environment for GPUoffload. This arrangement allows the host processor 405 software tosetup operands and access computation results, without the overhead oftradition I/O DMA data copies. Such traditional copies involve drivercalls, interrupts and memory mapped I/O (MMIO) accesses that are allinefficient relative to simple memory accesses. At the same time, theability to access GPU attached memory 420-423 without cache coherenceoverheads can be critical to the execution time of an offloadedcomputation. In cases with substantial streaming write memory traffic,for example, cache coherence overhead can significantly reduce theeffective write bandwidth seen by a GPU 410-413. The efficiency ofoperand setup, the efficiency of results access, and the efficiency ofGPU computation all play a role in determining the effectiveness of GPUoffload.

In one implementation, the selection between GPU bias and host processorbias is driven by a bias tracker data structure. A bias table may beused, for example, which may be a page-granular structure (i.e.,controlled at the granularity of a memory page) that includes 1 or 2bits per GPU-attached memory page. The bias table may be implemented ina stolen memory range of one or more GPU-attached memories 420-423, withor without a bias cache in the GPU 410-413 (e.g., to cachefrequently/recently used entries of the bias table). Alternatively, theentire bias table may be maintained within the GPU.

In one implementation, the bias table entry associated with each accessto the GPU-attached memory 420-423 is accessed prior the actual accessto the GPU memory, causing the following operations. First, localrequests from the GPU 410-413 that find their page in GPU bias areforwarded directly to a corresponding GPU memory 420-423. Local requestsfrom the GPU that find their page in host bias are forwarded to theprocessor 405 (e.g., over a high-speed link as discussed above). In oneembodiment, requests from the processor 405 that find the requested pagein host processor bias complete the request like a normal memory read.Alternatively, requests directed to a GPU-biased page may be forwardedto the GPU 410-413. The GPU may then transition the page to a hostprocessor bias if it is not currently using the page.

The bias state of a page can be changed either by a software-basedmechanism, a hardware-assisted software-based mechanism, or, for alimited set of cases, a purely hardware-based mechanism.

One mechanism for changing the bias state employs an API call (e.g.,OpenCL), which, in turn, calls the GPU's device driver which, in turn,sends a message (or enqueues a command descriptor) to the GPU directingit to change the bias state and, for some transitions, perform a cacheflushing operation in the host. The cache flushing operation is requiredfor a transition from host processor 405 bias to GPU bias, but is notrequired for the opposite transition.

In one embodiment, cache coherency is maintained by temporarilyrendering GPU-biased pages uncacheable by the host processor 405. Toaccess these pages, the processor 405 may request access from the GPU410 which may or may not grant access right away, depending on theimplementation. Thus, to reduce communication between the processor 405and GPU 410 it is beneficial to ensure that GPU-biased pages are thosewhich are required by the GPU but not the host processor 405 and viceversa.

Graphics Processing Pipeline

FIG. 5 illustrates a graphics processing pipeline 500, according to anembodiment. In one embodiment, a graphics processor can implement theillustrated graphics processing pipeline 500. The graphics processor canbe included within the parallel processing subsystems as describedherein, such as the parallel processor 200 of FIG. 2A, which, in oneembodiment, is a variant of the parallel processor(s) 112 of FIG. 1. Thevarious parallel processing systems can implement the graphicsprocessing pipeline 500 via one or more instances of the parallelprocessing unit (e.g., parallel processing unit 202 of FIG. 2A) asdescribed herein. For example, a shader unit (e.g., graphicsmultiprocessor 325 of FIG. 3A) may be configured to perform thefunctions of one or more of a vertex processing unit 504, a tessellationcontrol processing unit 508, a tessellation evaluation processing unit512, a geometry processing unit 516, and a fragment/pixel processingunit 524. The functions of data assembler 502, primitive assemblers 506,514, 518, tessellation unit 510, rasterizer 522, and raster operationsunit 526 may also be performed by other processing engines within aprocessing cluster (e.g., processing cluster 214 of FIG. 2A) and acorresponding partition unit (e.g., partition unit 220A-220N of FIG.2A). The graphics processing pipeline 500 may also be implemented usingdedicated processing units for one or more functions. In one embodiment,one or more portions of the graphics processing pipeline 500 can beperformed by parallel processing logic within a general purposeprocessor (e.g., CPU). In one embodiment, one or more portions of thegraphics processing pipeline 500 can access on-chip memory (e.g.,parallel processor memory 222 as in FIG. 2A) via a memory interface 528,which may be an instance of the memory interface 218 of FIG. 2A.

In one embodiment, the data assembler 502 is a processing unit thatcollects vertex data for surfaces and primitives. The data assembler 502then outputs the vertex data, including the vertex attributes, to thevertex processing unit 504. The vertex processing unit 504 is aprogrammable execution unit that executes vertex shader programs,lighting and transforming vertex data as specified by the vertex shaderprograms. The vertex processing unit 504 reads data that is stored incache, local or system memory for use in processing the vertex data andmay be programmed to transform the vertex data from an object-basedcoordinate representation to a world space coordinate space or anormalized device coordinate space.

A first instance of a primitive assembler 506 receives vertex attributesfrom the vertex processing unit 504. The primitive assembler 506readings stored vertex attributes as needed and constructs graphicsprimitives for processing by tessellation control processing unit 508.The graphics primitives include triangles, line segments, points,patches, and so forth, as supported by various graphics processingapplication programming interfaces (APIs).

The tessellation control processing unit 508 treats the input verticesas control points for a geometric patch. The control points aretransformed from an input representation from the patch (e.g., thepatch's bases) to a representation that is suitable for use in surfaceevaluation by the tessellation evaluation processing unit 512. Thetessellation control processing unit 508 can also compute tessellationfactors for edges of geometric patches. A tessellation factor applies toa single edge and quantifies a view-dependent level of detail associatedwith the edge. A tessellation unit 510 is configured to receive thetessellation factors for edges of a patch and to tessellate the patchinto multiple geometric primitives such as line, triangle, orquadrilateral primitives, which are transmitted to a tessellationevaluation processing unit 512. The tessellation evaluation processingunit 512 operates on parameterized coordinates of the subdivided patchto generate a surface representation and vertex attributes for eachvertex associated with the geometric primitives.

A second instance of a primitive assembler 514 receives vertexattributes from the tessellation evaluation processing unit 512, readingstored vertex attributes as needed, and constructs graphics primitivesfor processing by the geometry processing unit 516. The geometryprocessing unit 516 is a programmable execution unit that executesgeometry shader programs to transform graphics primitives received fromprimitive assembler 514 as specified by the geometry shader programs. Inone embodiment, the geometry processing unit 516 is programmed tosubdivide the graphics primitives into one or more new graphicsprimitives and calculate parameters used to rasterize the new graphicsprimitives.

In some embodiments the geometry processing unit 516 can add or deleteelements in the geometry stream. The geometry processing unit 516outputs the parameters and vertices specifying new graphics primitivesto primitive assembler 518. The primitive assembler 518 receives theparameters and vertices from the geometry processing unit 516 andconstructs graphics primitives for processing by a viewport scale, cull,and clip unit 520. The geometry processing unit 516 reads data that isstored in parallel processor memory or system memory for use inprocessing the geometry data. The viewport scale, cull, and clip unit520 performs clipping, culling, and viewport scaling and outputsprocessed graphics primitives to a rasterizer 522.

The rasterizer 522 can perform depth culling and other depth-basedoptimizations. The rasterizer 522 also performs scan conversion on thenew graphics primitives to generate fragments and output those fragmentsand associated coverage data to the fragment/pixel processing unit 524.The fragment/pixel processing unit 524 is a programmable execution unitthat is configured to execute fragment shader programs or pixel shaderprograms. The fragment/pixel processing unit 524 transforming fragmentsor pixels received from rasterizer 522, as specified by the fragment orpixel shader programs. For example, the fragment/pixel processing unit524 may be programmed to perform operations included but not limited totexture mapping, shading, blending, texture correction and perspectivecorrection to produce shaded fragments or pixels that are output to araster operations unit 526. The fragment/pixel processing unit 524 canread data that is stored in either the parallel processor memory or thesystem memory for use when processing the fragment data. Fragment orpixel shader programs may be configured to shade at sample, pixel, tile,or other granularities depending on the sampling rate configured for theprocessing units.

The raster operations unit 526 is a processing unit that performs rasteroperations including, but not limited to stencil, z test, blending, andthe like, and outputs pixel data as processed graphics data to be storedin graphics memory (e.g., parallel processor memory 222 as in FIG. 2,and/or system memory 104 as in FIG. 1, to be displayed on the one ormore display device(s) 110 or for further processing by one of the oneor more processor(s) 102 or parallel processor(s) 112. In someembodiments the raster operations unit 526 is configured to compress zor color data that is written to memory and decompress z or color datathat is read from memory.

Light Field Displays

Turning now to FIG. 6A, a light field display system 600 is shown inwhich a plurality of display planes 602 (602 a-602 c) are arranged in astacked configuration. Each display plane 602 may correspond to, forexample, a liquid crystal display (LCD) panel in a stacked arrangementof LCD panels. The light field display system 600 may be incorporatedinto a near-eye device such as, for example, a head mounted display(HMD) device (not shown) that presents three-dimensional (3D) virtualreality (VR) and/or augmented reality (AR) content to a wearer (e.g.,user) of the HMD device. The 3D content may be simulated (e.g.,resulting from execution of a multi-player game application), cinematic(e.g., resulting from a video/image capture), or any combinationthereof. An enhanced graphics processor 604 (e.g., graphics processingunit/GPU) may compose the 3D content as a light field that, whenrendered to the display planes 602, provides focus cues that reducevisual discomfort to the wearer. More particularly, the display planes602 may modulate a uniform backlight in a multiplicative fashion sothat, when observed through lenses, the display planes 602 provide focuscues in addition to binocular disparity.

The illustrated graphics processor 604 includes logic 606 (e.g., logicinstructions, configurable logic, fixed-functionality hardware logic,etc., or any combination thereof) to perform re-projection, foveation,tile binning, image warping and more efficient data formatting. As willbe discussed in greater detail, the graphics processor 604 may beconsidered to be enhanced to the extent that operation of the logic 604reduces latency, improves performance, reduces power consumption and/orextends battery life.

FIG. 6B demonstrates that the enhanced graphics processor 604 may be asemiconductor package apparatus that includes one or more substrates 608(e.g., silicon, sapphire, gallium arsenide) coupled to the logic 606(e.g., transistor array and other integrated circuit/IC components). Asalready noted, the logic 606 may be implemented at least partly inconfigurable logic or fixed-functionality logic hardware.

Data Formatting

Turning now to FIG. 6C, a plurality of display planes 610 (610 a-610 n)is shown. In general, content presented at a common pixel location 612(612 a-612 n) may be similar. In the illustrated example, image data(e.g., primitives/polygons, vertices, textures, colors, depthinformation) associated with the common pixel location 612 is stored toadjacent memory locations 614 (e.g., a single cache line). Bysimultaneously rendering the image data from the adjacent memorylocations 614 across the plurality of display planes 610, significantlatency reductions may be achieved. For example, if 3D content to bepresented on the display planes 610 includes a nature scene containing abird, the bird may be in approximately the same x, y coordinate locationin each of the display planes 610. Thus, the same image data may beretrieved only once and re-used across the plurality of display planes610, rather than evicting the image data from memory (e.g., cache) andretrieving it again each time the scene is processed for a differentdisplay plane 610.

Indeed, a single instruction multiple data (SIMD) instruction may bedispatched to a plurality of graphics execution units to simultaneouslyrender the image data. Moreover, the image data may be associated with apixel subspan (e.g., 2×2 pixel neighborhood) containing the common pixellocation 112, depending on the memory layout (e.g., cache line size)and/or SIMD instruction width.

FIG. 6D shows a method 616 of managing image data. The method 616 maygenerally be implemented in logic such as, for example, the logic 606(FIGS. 6A and 6B), already discussed. More particularly, the method 616may be implemented as one or more modules in a set of logic instructionsstored in a machine- or computer-readable storage medium such as randomaccess memory (RAM), read only memory (ROM), programmable ROM (PROM),firmware, flash memory, etc., in configurable logic such as, forexample, programmable logic arrays (PLAs), field programmable gatearrays (FPGAs), complex programmable logic devices (CPLDs), infixed-functionality hardware logic using circuit technology such as, forexample, application specific integrated circuit (ASIC), complementarymetal oxide semiconductor (CMOS) or transistor-transistor logic (TTL)technology, or any combination thereof.

For example, computer program code to carry out operations shown in themethod 616 may be written in any combination of one or more programminglanguages, including an object oriented programming language such asJAVA, SMALLTALK, C++ or the like and conventional procedural programminglanguages, such as the “C” programming language or similar programminglanguages. Additionally, logic instructions might include assemblerinstructions, instruction set architecture (ISA) instructions, machineinstructions, machine dependent instructions, microcode, state-settingdata, configuration data for integrated circuitry, state informationthat personalizes electronic circuitry and/or other structuralcomponents that are native to hardware (e.g., host processor, centralprocessing unit/CPU, microcontroller, etc.).

Illustrated processing block 618 provides for identifying a pixellocation with respect to a plurality of display planes. Image dataassociated with the pixel location and the plurality of display planesmay be stored to adjacent memory locations at block 620. In one example,the adjacent memory locations are contained within a single cache line.Additionally, the image data may be associated with a pixel subspancontaining the pixel location. Illustrated block 622 simultaneouslyrenders the image data from the adjacent memory locations across theplurality of display planes. Block 622 may include dispatching a SIMDinstruction to a plurality of graphics execution units. Block 624 mayoptionally transpose the simultaneously rendered image data to a surfacelayout associated with the plurality of display planes. For example, ifthe interface to the display panels calls for display scanout operationsto retrieve all data for a given display plane before retrieving datafor the next display plane, block 624 might include re-arranging therendered image data in memory to align with the expectations of theinterface.

FIG. 6E shows a method 626 of conducting a memory setup procedure. Themethod 626 may generally be implemented in logic such as, for example,the logic 606 (FIGS. 6A and 6B), already discussed. More particularly,the method 626 may be implemented as one or more modules in a set oflogic instructions stored in a machine- or computer-readable storagemedium such as RAM, ROM, PROM, firmware, flash memory, etc., inconfigurable logic such as, for example, PLAs, FPGAs, CPLDs, infixed-functionality hardware logic using circuit technology such as, forexample, ASIC, CMOS or TTL technology, or any combination thereof. Inthe illustrated example, an application creates displayable planes forlight field display at processing block 628 via a 3D applicationprogramming interface (API). Additionally, a user mode driver (UMD) maycreate a memory allocation for the displayable planes at block 630. Inthe illustrated example, the memory allocation corresponds to theenhanced memory layout (e.g., data format) described herein.

FIG. 6F shows a more detailed method 632 of managing image data. Themethod 632 may generally be implemented in logic such as, for example,the logic 606 (FIGS. 6A and 6B), already discussed. More particularly,the method 632 may be implemented as one or more modules in a set oflogic instructions stored in a machine- or computer-readable storagemedium such as RAM, ROM, PROM, firmware, flash memory, etc., inconfigurable logic such as, for example, PLAs, FPGAs, CPLDs, infixed-functionality hardware logic using circuit technology such as, forexample, ASIC, CMOS or TTL technology, or any combination thereof.

In the illustrated example, an application submits draw requests atprocessing block 634 via a 3D API. Block 636 may submit a draw to agraphics processor, wherein the graphics processor may perform pipelineoperations such as, for example, vertex fetching (VF), vertex shading(VS), clipping (CL), rasterization, etc., at block 638. Additionally,when the draw is broken into individual pixels (or 2×2 subspans ofpixels), illustrated block 640 may submit each pixel to the parallelexecution units across multiple display planes simultaneously. Forexample, if the execution units support SIMD8 dispatch, block 640 maysubmit eight pixels from eight different display planes in a singlethread dispatch. At illustrated block 642, the draw work may completeand additional frame rendering may continue.

Thus, FIGS. 6C-6F demonstrate that enhanced data formatting technologymay use more efficient data storage and thread dispatches to achievereduced latency, increased performance in systems containing light fielddisplays. Moreover, the increased performance may lead to less powerconsumption and longer battery life.

Re-Projection

Turning now to FIG. 7A, a source view 644 (e.g., viewport, rendertarget) and a re-projected view 646 are shown. The source view 644 maybe associated with a first display plane in a plurality of displayplanes, whereas the re-projected view 646 may be associated with asecond (e.g., different) display plane in the plurality of displayplanes. The re-projected view 646 may generally be generated from thesource view 644 rather than rendering the re-projected view 646 from“scratch”. In the illustrated example, the re-projected view 646includes a “hole” 648 (e.g., region missing color, texture or otherimage data). The hole 648 may be the result of a slight differencebetween the position of 3D content presented on the first display planeand the position of the same 3D content presented on the second displayplane. As will be discussed in greater detail, a number of enhancedre-projection techniques may be used to “fill” (e.g., determine imagedata for) the hole 648. For example, the hole 648 may be filled in basedon extended field of view data 650 corresponding to the source view 644,rasterization data 652 corresponding to the source view 644,rasterization data 654 associated with the re-projected view 646, or anycombination thereof.

FIG. 7B shows a method 656 of enhancing re-projected views. The method656 may generally be implemented in logic such as, for example, thelogic 606 (FIGS. 6A and 6B), already discussed. More particularly, themethod 656 may be implemented as one or more modules in a set of logicinstructions stored in a machine- or computer-readable storage mediumsuch as RAM, ROM, PROM, firmware, flash memory, etc., in configurablelogic such as, for example, PLAs, FPGAs, CPLDs, in fixed-functionalityhardware logic using circuit technology such as, for example, ASIC, CMOSor TTL technology, or any combination thereof.

Illustrated processing block 658 provides for rendering a source viewassociated with a first display plane in a plurality of display planes,wherein the rendered source view may be re-projected to a second displayplane in the plurality of display planes at block 660. The result ofblock 660 may be a re-projected view such as, for example, there-projected view 646 (FIG. 7A), already discussed.

One or more holes in the re-projected view may be filled in at block 662based on one or more of extended field of view data corresponding to thesource view, rasterization data corresponding to the source view orrasterization data corresponding to the re-projected view. As will bediscussed in greater detail, when the hole(s) are filled based onextended field of view data, the re-projected view may have anon-extended (e.g., standard) field of view. Moreover, when the hole(s)are filled based on rasterization data corresponding to the source view,a depth test may be disabled during rendering of the source view, withthe depth test being conducted during filling of the hole(s) in there-projected view. Additionally, when the hole(s) are filled based onthe rasterization data corresponding to the re-projected view, a depthbuffer may be pre-populated during re-projection of the rendered sourceview, wherein a depth test may be conducted during filling of thehole(s) based on data in the depth buffer.

FIG. 7C shows a conventional re-projection 664 in comparison with anenhanced re-projection 666. In the illustrated example, a view frustum668 in the conventional re-projection 664 defines a standard field ofview for a source view 670. Accordingly, a re-projected view 672 in theconventional re-projection 664 may contain one or more holes 674. Bycontrast, a view frustum 676 in the enhanced re-projection 666 maydefine an extended (e.g., substantially wider) field of view for asource view 678. Using image data 680 from the extended field of view tofill in the one or more holes 674 may therefore enable a re-projectedview 682 to be generated from the source view 678. The illustratedre-projected view 682 has a non-extended field of view.

FIG. 7D shows a method 684 of filling view holes based on rasterizationdata corresponding to a source view. The method 684 generallydemonstrates that a depth test may be disabled during rendering of thesource view, wherein the depth test may be conducting during the fillingin of the holes in a re-projected view. Thus, every primitive in thesource view may be fully shaded in the illustrated solution. The method684 may generally be implemented in logic such as, for example, thelogic 606 (FIGS. 6A and 6B), already discussed. More particularly, themethod 684 may be implemented as one or more modules in a set of logicinstructions stored in a machine- or computer-readable storage mediumsuch as RAM, ROM, PROM, firmware, flash memory, etc., in configurablelogic such as, for example, PLAs, FPGAs, CPLDs, in fixed-functionalityhardware logic using circuit technology such as, for example, ASIC, CMOSor TTL technology, or any combination thereof.

Illustrated processing block 686 conducts a mesh rasterization for allprimitives associated with a source view. An input assembly may beconducted at block 688, wherein illustrated block 690 conducts vertexshading operations. Rasterization may be passed to an offscreen surfaceat block 692. Accordingly, depth information for each pixel may bestored to an offscreen rasterization depth buffer 694. Additionally,illustrated block 696 conducts pixel shading operations. In theillustrated example, color information for each pixel may be stored toan offscreen rasterization color buffer 698. Block 700 may conductshader stage re-projection and depth testing operations, wherein colorand depth writes to additional view buffers 702 may be conducted whenthe depth test passes (e.g., the vertex is visible).

FIG. 7E shows a method 704 of filling view holes based on rasterizationdata corresponding to a re-projected view. The method 704 generallydemonstrates that a depth buffer may be pre-populated duringre-projection of a rendered source view, with a depth test beingconducting during filling of the hole(s) based on data in the depthbuffer. The method 704 may generally be implemented in logic such as,for example, the logic 606 (FIGS. 6A and 6B), already discussed. Moreparticularly, the method 704 may be implemented as one or more modulesin a set of logic instructions stored in a machine- or computer-readablestorage medium such as RAM, ROM, PROM, firmware, flash memory, etc., inconfigurable logic such as, for example, PLAs, FPGAs, CPLDs, infixed-functionality hardware logic using circuit technology such as, forexample, ASIC, CMOS or TTL technology, or any combination thereof.

Illustrated processing block 706 provides for clearing the color of are-projected (e.g., “View 1”). Additionally, the depth of there-projected view may be cleared at block 708. Block 710 may re-project,for each pixel in the render target, depth information from a sourceview (e.g., “View 0”). Additionally, geometry may be rendered to View 1at block 712, wherein a determination may be made at block 714 as towhether each pixel passes the depth test. If the pixel passes the depthtest, illustrated block 716 renders the pixel. Otherwise, block 718 maydo nothing.

Thus, FIGS. 7A-7E demonstrate that enhanced re-projection technology mayuse pre-existing image data to eliminate visual artifacts in systemscontaining light field displays while maintaining high performance.Indeed, the enhanced re-projection technology may be combined with thedata formatting technology described with respect to FIGS. 6C-6F toachieve synergistic improvements with regard to latency, performance,power consumption and/or battery life. For example, the image datacorresponding to source views may be stored more efficiently and used tooptimize thread dispatches.

Foveation

Fovea may refer to a small depression in the retina of the eye wherevisual acuity may be highest. The center of the field of vision may befocused in this region, where retinal cones may be particularlyconcentrated. In the context of some graphics applications, a fovea or afoveated region may correspond to an area of focus in an image ordisplay.

FIG. 8A shows a foveated view layout 720 in which a foveated region 722in the field of view of a user corresponds to a focus point of the user.The illustrated foveated region 722 is surrounded by a peripheral (e.g.,out-of-focus) region 724. As will be described in greater detail, scenecontent presented on a plurality of display planes may be varied on aper display plane basis using the focus point. For example, the imageresolution of one or more fovea views 726 (e.g., cameras) in thefoveated region 722 may be set to relatively high values, wherein theimage resolution values are established independently for each displayplane. By contrast, the image resolution of one or more peripheral views728 (e.g., cameras) in the peripheral region 724 may be set torelatively low resolution values, wherein the image resolution valuesare also established independently for each display plane. The lowerimage resolution in the peripheral region 724 may reduce processingoverhead (e.g., rendering effort) without negatively impacting theperceived image quality because the human eye visual system is lesssensitive in the peripheral region 724.

In another example, the view density (e.g., number of views per squarearea) of the fovea views 726 in the foveated region 722 may be set to arelatively high value, wherein the view density is establishedindependently for each display plane. By contrast, the view density ofthe illustrated peripheral views 728 in the peripheral region 724 is setto a relatively low value, wherein the view density may be establishedindependently for each display plane. The lower view density in theperipheral region 724 may further reduce processing overhead withoutnegatively impacting the perceived image quality because of less eyesensitivity in the peripheral region 724.

Moreover, the view update frequency of the fovea views 726 in thefoveated region 722 may be set (e.g., independently for each displayplane) to a relatively high value, whereas the view update frequency ofthe peripheral views 728 in the peripheral region 724 might be set(e.g., independently for each display plane) to a relatively low value.Again, the lower view update frequency in the peripheral region 724 mayfurther reduce processing overhead without negatively impacting theperceived image quality.

FIG. 8B shows a method 730 of foveating scene content presented on aplurality of display planes. The method 730 may generally be implementedin logic such as, for example, the logic 606 (FIGS. 6A and 6B), alreadydiscussed. More particularly, the method 730 may be implemented as oneor more modules in a set of logic instructions stored in a machine- orcomputer-readable storage medium such as RAM, ROM, PROM, firmware, flashmemory, etc., in configurable logic such as, for example, PLAs, FPGAs,CPLDs, in fixed-functionality hardware logic using circuit technologysuch as, for example, ASIC, CMOS or TTL technology, or any combinationthereof.

Illustrated processing block 732 provides for determining a focus pointrelative to a plurality of display planes. Block 732 may includeobtaining eye position information from an eye tracker (e.g., cameracapturing the eyes of the user). The eye tracker may use informationfrom a sensor hub, motion monitor and/or other sources to provide focusinformation. The focus information may include, for example, the focuspoint, a focus area, an eye position, eye motion, pupil size, pupildilation, depth of focus (DOF), a content focal point, a content focusobject, a content focus area, etc. The focus information may alsoinclude prior focus information, determined future focus information,and/or predicted focus information (e.g., a predicted focal point, apredicted focus area, a predicted eye position, predicted eye motion,predicted pupil size, predicted pupil dilation, predicted DOF,determined future content focal point, determined future content focusobject, determined future content focus area, predicted content focalpoint, predicted content focus object, predicted content focus area,etc.).

Block 734 may vary, on a per display plane basis, the resolution ofscene content presented on the plurality of display planes based on thefocus point. Block 734 may include, for example, increasing theresolution in a foveated region and decreasing the resolution in aperipheral region. Additionally, illustrated block 736 varies, on theper display plane basis, the view density of scene content presented onthe plurality of display planes based on the focus point. Block 736 maytherefore include increasing the view density in the foveated region anddecreasing the view density in the peripheral region. The view updatefrequency of scene content presented on the plurality of display planesmay be varied at block 738, on the per display plane basis, based on thefocus point. Block 738 may include increasing the view update frequencyin the foveated region and decreasing the view update frequency in theperipheral region.

Illustrated block 740 separates peripheral views into bins having one ormore of different resolutions, different view densities or differentupdate frequencies. With continuing reference to FIGS. 8B and 8C, afoveated view layout 742 is shown in which a peripheral region 744contains a first bin 746 (bin “A”), a second bin 748 (bin “B”) and athird bin 750 (bin “C”). The bins 746, 748, 750 may be associated withperipheral views having different resolutions, view densities and/orupdate frequencies. For example, peripheral views having a relativelyhigh image resolution may be assigned to the first bin 746, peripheralviews having a relatively low image resolution may assigned to the thirdbin 750, and peripheral views having an intermediate image resolutionmay be assigned to the second bin 748. Because the light field displaymay present a large number of peripheral views that are updated ondifferent frames (e.g., some views may be updated on frame n other viewsmay be updated on frame n+1, and still other views might be updated onframe n+2), even if there is a slight change in the focus point, thereis a high likelihood that at least one of the views will capture anycontent change that results.

The peripheral views may be similarly separated into bins havingdifferent view densities. For example, the first bin 746 might beprovided with more locations in the peripheral region 744 than thesecond bin 748, which may in turn be provided with more locations in theperipheral region 744 than the third bin 750. In yet another example,peripheral views having a relatively high update frequency may assignedto the first bin 746, peripheral views having a relatively low updatefrequency may be assigned to the third bin 750, and peripheral viewshaving an intermediate resolution may be assigned to the second bin 748.

Alternatively, a view warping technique may be used for views that arenot to be fully updated within a frame. For example, for some N numberof frames, a view V may be fully updated. During some or all of thenon-full-update frames, the view V may be created by re-using image data(e.g., warping) from either adjacent views or the previous full-updateframe.

Moreover, using knowledge of the layout of the multiple views, a tilerenderer may be further optimized for geometry binning. For example,finer grained checks may be used earlier in concentrated regions such asthe foveated region 722 (FIG. 8A). As another example, the frustum shapemay be modified based on which views are being updated during aparticular frame.

FIGS. 8A-8C therefore demonstrate that enhanced foveation technology mayreduce rendering effort in light field displays on a per display planebasis without negatively impacting the perceived image quality.Moreover, the enhanced foveation technology may be combined with thedata formatting technology described with respect to FIGS. 6C-6F and/orthe enhanced re-projection technology described with respect to FIGS.7A-7E to achieve additional synergistic improvements with regard tolatency, performance, power consumption and/or battery life. Forexample, the image data associated with the foveated region views and/orthe peripheral region views may be stored more efficiently and used tooptimize thread dispatches. Additionally, the re-projection techniquesdescribed herein may be readily applied to the foveated region viewsand/or the peripheral region views.

Tile Binning

In light field displays, the number of views (e.g., viewports, rendertargets) may be much greater than in conventional displays. Accordingly,determining which geometry (e.g., primitives, polygons) from the viewsto accept and rasterize or reject and discard may present a renderingbottleneck challenge. Technology described herein may use hierarchicalculling operations and tile bins to reduce and/or eliminate renderingbottlenecks in light field displays.

FIG. 9A shows a view layout 752 that is organized into a plurality oftiles (tile “TIA” to tile “T3D”). The illustrated view layout 752, whichis merely an example, may vary in resolution, viewport count, tile size,etc., depending on the circumstances. Each tile may have a size of, forexample, 256×256 pixels. Accordingly, the 4×3 array of tiles may resultin a view size of, for example, 1024×768 pixels. A plan (e.g., top) viewof a view frustum 754 demonstrates the relationship of the view layout752 to the eye of the user.

FIG. 9B shows a left eye collection 756 of 8×6 views (view “L1A” to view“L4F”) and a right eye collection 758 of 8×6 views. (view “R1A” to view“R4F”). The views may be organized into either an aligned array 760 ofdisplay plane frustums or a non-aligned (e.g., curved) array 762 ofdisplay plane frustums. The collections 756, 758 demonstrate that alight field display may involve processing primitives for a large numberof views. Rather than processing each primitive for all views (e.g., 48views*12 tiles per view), hierarchical culling operations and tile binsmay be used as described herein.

Turning now FIG. 9C, a method 764 of managing primitives associated witha plurality of display planes is shown. The method 764 may generally beimplemented in logic such as, for example, the logic 606 (FIGS. 6A and6B), already discussed. More particularly, the method 764 may beimplemented as one or more modules in a set of logic instructions storedin a machine- or computer-readable storage medium such as RAM, ROM,PROM, firmware, flash memory, etc., in configurable logic such as, forexample, PLAs, FPGAs, CPLDs, in fixed-functionality hardware logic usingcircuit technology such as, for example, ASIC, CMOS or TTL technology,or any combination thereof. Illustrated processing block 766 providesfor determining a set of primitives associated with a plurality ofdisplay planes. Additionally, a hierarchical sequence of cullingoperations may be conducted on the set of primitives at block 768.

FIG. 9D demonstrates that the hierarchical sequence may begin with anear plane-far plane culling operation. Thus, with regard to the alignedarray 760, the near plane-far plane culling operation may rejectprimitives behind a farthest display plane 770 and reject primitives infront of a nearest display plane 772. Similarly, with regard to thenon-aligned array 762, the near plane-far plane culling operation mayreject primitives behind a farthest display plane 774 and rejectprimitives in front of a nearest display plane 776.

FIG. 9E demonstrates that after the near plane-far plane cullingoperation, a coarse frustum culling operation may be conducted on a pereye basis. More particularly, the coarse frustum culling operation mightinvolve selecting an eye (e.g., left eye), determining a left frustumplane 778 of a leftmost viewport 780 (e.g., view) and determining aright frustum plane 782 of a rightmost viewport 784. The illustratedcoarse frustum culling operation involves determining a top frustumplane of a topmost viewport (not shown), determining a bottom frustumplane of a bottommost viewport, and rejecting primitives outside the topfrustum plane, the bottom frustum plane, the left frustum plane 778 andthe right frustum plane 782. In one example, the rejection testcalculates a distance between the vertices of each primitive and eachfrustum plane to determine the relative position of the primitive to theplane in question. The illustrated approach may be repeated for theright eye.

Turning now to FIGS. 9F and 9G, fine frustum culling determinations areillustrated in which the primitives are assigned to tile bins. In theillustrated example, a binary reject operation determines whether aprimitive is within a left set 786 of frustums or a right set 788 offrustums. If, for example, a primitive is found to be within the leftset 786 of frustums, a further check may be performed to determine ifthe primitive is within a rightmost frustum 790 of the left set 786. Ifthe primitive is found to be within the rightmost frustum 790, the tilebins associated with the rightmost frustum 790 may be populated with theprimitive in question. While the left set 786 and the right set 788 andare shown in the illustrated example, the fine frustum cullingdeterminations may also include similar checks that are performed for atop set (not shown) of frustums and a bottom set (not shown) offrustums.

FIG. 9H shows a method 792 of conducting a hierarchical sequence ofculling operations. The method 792 may generally be implemented in logicsuch as, for example, the logic 606 (FIGS. 6A and 6B), alreadydiscussed. More particularly, the method 792 may be implemented as oneor more modules in a set of logic instructions stored in a machine- orcomputer-readable storage medium such as RAM, ROM, PROM, firmware, flashmemory, etc., in configurable logic such as, for example, PLAs, FPGAs,CPLDs, in fixed-functionality hardware logic using circuit technologysuch as, for example, ASIC, CMOS or TTL technology, or any combinationthereof.

Illustrated processing block 794 provides for conducting a nearplane-far plane culling operation that rejects primitives behind afarthest display plane in the plurality of display planes and rejectsprimitives in front of a nearest display plane in the plurality ofdisplay planes. Additionally, block 796 may conduct, on a per eye basisand after the near plane-far plane culling operation, a coarse frustumculling operation that rejects primitives outside a top frustum plane ofa topmost viewpoint, a bottom frustum plane of a bottommost viewport, aleft frustum plane of a leftmost viewport and a right frustum plane of arightmost viewport. In one example, a fine frustum culling operation isconducted at block 798 after the coarse frustum culling operation andblock 800 may populate one or more tile bins with primitives that passthe fine frustum culling operation.

An alternative simple approach may be done for all viewport frustumplane sets that are parallel. Hardware may implement a plane equationfor the left, right, top, and bottom planes of the view frustums. Thisapproach can be done for the frustum planes of the viewportsrepresenting the same relative bin offsets (e.g., the planes areparallel, and only differ by an offset from the origin). Each viewfrustum may be represented with a different distance from the origin.When primitives are tested for inclusion the following check may beperformed:

Bool PlaneCheck(Polygon, Plane)

For (each point in polygon):

If(dot(Plane.Normal, point)<Plane.Distance)

Return TRUE;

Return FALSE;

Using the left eye planes of FIG. 9B as an example, the planes may allshare the normal, and may only differ by an offset. For example, theleft planes for viewports L1A, L2A, L1B, . . . L2B may have thefollowing plane properties:

LeftPlaneL1A=LeftPlane.Normal, LeftPlaneL1A_Offset

LeftPlaneL2A=LeftPlane.Normal, LeftPlaneL2A_Offset

LeftPlaneL1B=LeftPlane.Normal, LeftPlaneL1B_Offset

. . .

LeftPlaneL2B=LeftPlane.Normal, LeftPlaneL1B_Offset

This pattern may apply to all viewports for both eyes.

The same may be true for tiles within the same viewports (e.g., eachtile within a viewport will have a different plane Normal, but all tilesmay be uniform across all render targets). For example, with referenceto FIGS. 9A and 9B, the plane equation for tile T1A in L1A, L2A, L1B, .. . L2B may be:

LeftPlaneL1A_T1A=T1A_LeftPlane.Normal, LeftPlaneL1A_T1A_Offset

LeftPlaneL2A_T1A=T1A_LeftPlane.Normal, LeftPlaneL2A_T1A_Offset

LeftPlaneL1B_TIA=T1A_LeftPlane.Normal, LeftPlaneL1B_T1A_Offset

. . .

LeftPlaneL2B_T1A=T1A_LeftPlane.Normal, LeftPlaneL1B_T1A_Offset

In the end for inclusion, a dot product may be performed between allvertices in a primitive and the Normal of each left, right, top, andbottom planes. Individual viewport checks may be performed with only theplane offset comparisons.

To perform frustum checks for all T1A tiles in all viewports in the lefteye using this approach, the following may be used:

//define a function pointer type use different comparator: > (for leftand bottom), > (for right and top) typedef bool(CompareOperator*)(float, float); //define the compartor functions boolCompareOperatorGreaterThan(float offsetFromOrigin, floatplaneOffsetFromOrigin) {return offsetFromOrigin > planeOffsetFromOrigin;} bool CompareOperatorLessThan(float offsetFromOrigin, floatplaneOffsetFromOrigin) {return offsetFromOrigin < planeOffsetFromOrigin;} //helper function to see if any point in a polygon passes the planecheck bool AnyPointPassesPlaneCheck(FloatVector polygonOffsets, Float3planeNormal, float planeOffset, CompareOperator compareOp) { boolanyPointsPass = false; for (pointOffset all offsets in polygonOffsets) {if (compareOp(pointOffset, planeOffset)) { a. anyPointsPass = true; b.break; } } return anyPointsPass; } //define the planes enum Plane{Left,Right, Top, Bottom, PlaneCount = 4 } Void MultiFrustumCheck(Polygonpolygon, BOOL passResults]6][4], Float3planesNormalsPerTile[PlaneCount], Float3Vector< PlaneCount >offsetsPerViewport[6][4], CompareOperator compareFuns[PlaneCount]) {FloatVector polygonOffsets[PlaneCount]; //collect offsets per polygonper plane for (all points in Polygon) {polygonOffsets[Left].Append(dot(point, planesNormalsPerTile[Left]);polygonOffsets[Right].Append(dot(point, planesNormalsPerTile[Right]);polygonOffsets[Top].Append(dot(point, planesNormalsPerTile[Top]);polygonOffsets[Bottom].Append(dot(point, planesNormalsPerTile[Bottom]);{ // for (int x = 0; x < 6; ++x) { for (int y = 0; y < 4; ++y) { a. //inorder to fail the test there has to be one plane where all points failthe plane check b. passResults[x][y] =AnyPointPassesPlaneCheck(polygonOffsets[Left],planesNormalsPerTile[Left], offsetsPerViewport[x][y].Left,CompareOperatorGreaterThan) && i.AnyPointPassesPlaneCheck(polygonOffsets[Right],planesNormalsPerTile[Right], offsetsPerViewport[x][y].Right,CompareOperatorLessThan) && ii.AnyPointPassesPlaneCheck(polygonOffsets[Top], planesNormalsPerTile[Top],offsetsPerViewport[x][y].Top, CompareOperatorLessThan) && iii.AnyPointPassesPlaneCheck(polygonOffsets[Bottom],planesNormalsPerTile[Bottom], offsetsPerViewport[x][y].Bottom,CompareOperatorGreaterThan); } } }

It may be advantageous to cull primitives down to groups of tiles. Ifmost of the geometry is the same per tile in nearby viewports/rendertargets, the geometry may be sorted prior to rendering to avoidredundant pixel shader work. After the sort phase is done, the geometrymay be passed to the bin for each tile to be rasterized. The primitiverasterizer may still have the ability to early cull primitives that willnot result in rasterization work.

For example, an attempt might be made to rasterize work for tile T1D inviewports R1E-R4E and viewports R1F-R4F. FIG. 9I demonstrates a method802 that may represent the rendering process. The method 802 maygenerally be implemented in logic such as, for example, the logic 606(FIGS. 6A and 6B), already discussed. More particularly, the method 802may be implemented as one or more modules in a set of logic instructionsstored in a machine- or computer-readable storage medium such as RAM,ROM, PROM, firmware, flash memory, etc., in configurable logic such as,for example, PLAs, FPGAs, CPLDs, in fixed-functionality hardware logicusing circuit technology such as, for example, ASIC, CMOS or TTLtechnology, or any combination thereof.

The rendering pipeline may proceed at blocks 804, 806 and 808 byprocessing primitives (e.g., geometry, polygons) with a series oftrivial checks: near/far plane checks, and right eye coarse frustumchecks. Once the trivial checks are performed the range of tiles mayprovide plane equations at block 810 for left (from R1E), right (fromR1F), top (from R1E) and bottom (from R4E). These planes may haveoffsets and normals. Primitives may be tested at block 812 per vertexagainst these plane checks. If it is determined at block 814 that atleast one vertex per polygon passes, the primitive may be binned atblock 816. Otherwise, nothing is done at illustrated block 815. Themethod 802 may optionally sort the primitives at block 818 after theyare all binned. The primitives may then be passed to each tile'srasterizer at block 820. Illustrated block 822 rasterizes, for each tilebeing rendered, all primitives and rejects primitives outside the tile.

Another optimization may be to cull work as early as possible by addinga bounding sphere check through the pipeline to determine whichviewports might actually rasterize the object. The bounding sphere maybe trivially checked using the same near/far checks, coarse frustumchecks, and more detailed plane checks per range of tile. If thebounding sphere passes the check, then the entire mesh contained in thebounding sphere may be rendered.

FIGS. 9A-9I therefore demonstrate that enhanced tile binning technologymay enable a balance to be made between culling overhead and possiblystarving the rasterizer units. Moreover, the enhanced tile binningtechnology may be combined with the data formatting technology describedwith respect to FIGS. 6C-6F, the enhanced re-projection technologydescribed with respect to FIGS. 7A-7E and/or the enhanced foveationtechnology described with respect to FIGS. 8A-8C to achieve additionalsynergistic improvements with regard to latency, performance, powerconsumption and/or battery life.

Image Warping

FIG. 10A shows scene content 824 that may be warped across a pluralityof display planes. In general, position changes between the scenecontent 824 on different display planes may be used to approximate imagedata across the display planes.

With continuing reference to FIGS. 10A and 10B, a method 826 of warpingthe scene content 824 across a plurality of display planes is shown. Themethod 826 may generally be implemented in logic such as, for example,the logic 606 (FIGS. 6A and 6B), already discussed. More particularly,the method 826 may be implemented as one or more modules in a set oflogic instructions stored in a machine- or computer-readable storagemedium such as RAM, ROM, PROM, firmware, flash memory, etc., inconfigurable logic such as, for example, PLAs, FPGAs, CPLDs, infixed-functionality hardware logic using circuit technology such as, forexample, ASIC, CMOS or TTL technology, or any combination thereof.

Illustrated processing block 828 provides for identifying first imagedata associated with the scene content 824 on a first display plane inthe plurality of display planes. Block 830 may identify a first positionchange between the scene content 824 on the first display plane and thescene content 824 on a second display plane in the plurality of displayplanes. In one example, block 832 approximates, based on the first imagedata and the first position change, second image data associated withthe scene content 824 on the second display plane. Additionally, block834 may identify a second position change between the scene content 824on the first display plane and the scene content 824 on a third displayplane in the plurality of display planes. In such a case, illustratedblock 836 approximates, based on the first image data and the secondposition change, third image data associated with the scene content 824on the third display plane. Approximating the image data in the mannershown may significantly reduce processing overhead.

FIGS. 10A-10B therefore demonstrate that enhanced image warpingtechnology may render the same object from different positions on thefocal plane to mimic different focus points on the iris. Moreover, theenhanced image warping technology may be combined with the dataformatting technology described with respect to FIGS. 6C-6F, theenhanced re-projection technology described with respect to FIGS. 7A-7E,the enhanced foveation technology described with respect to FIGS. 8A-8Cand/or the enhanced tile binning technology described with respect toFIGS. 9A-9I to achieve additional synergistic improvements with regardto latency, performance, power consumption and/or battery life.

Display Technology

Turning now to FIG. 11, a performance-enhanced computing system 1100 isshown. In the illustrated example, a processor 1110 is coupled to adisplay 1120. The processor 1110 may generally generate images to bedisplayed on an LCD panel 1150 of the display 1120. In one example, theprocessor 1110 includes a communication interface such as, for example,a video graphics array (VGA), a DisplayPort (DP) interface, an embeddedDisplayPort (eDP) interface, a high-definition multimedia interface(HDMI), a digital visual interface (DVI), and so forth. The processor1110 may be a graphics processor (e.g., graphics processing unit/GPU)that processes graphics data and generates the images (e.g., videoframes, still images) displayed on the LCD panel 1150. Moreover, theprocessor 1110 may include one or more image processing pipelines thatgenerate pixel data. The image processing pipelines may comply with theOPENGL architecture, or other suitable architecture. Additionally, theprocessor 1110 may be connected to a host processor (e.g., centralprocessing unit/CPU), wherein the host processor executes one or moredevice drivers that control and/or interact with the processor 1110.

The illustrated display 1120 includes a timing controller (TCON) 1130,which may individually address different pixels in the LCD panel 1150and update each individual pixel in the LCD panel 1150 per refreshcycle. In this regard, the LCD panel 1150 may include a plurality ofliquid crystal elements such as, for example, a liquid crystal andintegrated color filter. Each pixel of the LCD panel 1150 may include atrio of liquid crystal elements with red, green, and blue color filters,respectively. The LCD panel 1150 may arrange the pixels in atwo-dimensional (2D) array that is controlled via row drivers 1152 andcolumn drivers 1154 to update the image being displayed by the LCD panel1150. Thus, the TCON 1130 may drive the row drivers 1152 and the columndrivers 1154 to address specific pixels of the LCD panel 1150. The TCON1130 may also adjust the voltage provided to the liquid crystal elementsin the pixel to change the intensity of the light passing through eachof the three liquid crystal elements and, therefore, change the color ofthe pixel displayed on the surface of the LCD panel 1150.

A backlight 1160 may include a plurality of light emitting elements suchas, for example, light emitting diodes (LEDs), that are arranged at anedge of the LCD panel 1150. Accordingly, the light generated by the LEDsmay be dispersed through the LCD panel 1150 by a diffuser (not shown).In another example, the LEDs are arranged in a 2D array directly behindthe LCD panel 1150 in a configuration sometimes referred to as directbacklighting because each LED disperses light through one or morecorresponding pixels of the LCD panel 1150 positioned in front of theLED. The light emitting elements may also include compact florescentlamps (CFL's) arranged along one or more edges of the LCD panel 1150. Toeliminate multiple edges, the combination of edges may be altered toachieve selective illumination of a region, wherein less than the totalset of lighting elements is used with less power.

The light emitting elements may also include one or more sheets ofelectroluminescent material placed behind the LCD panel 1150. In such acase, light from the surface of the sheet may be dispersed through thepixels of the LCD panel 1150. Additionally, the sheet may be dividedinto a plurality of regions such as, for example, quadrants. In oneexample, each region is individually controlled to illuminate only aportion of the LCD panel 1150. Other backlighting solutions may also beused.

The illustrated display 1120 also includes a backlight controller (BLC)1140 that provides a voltage to the light emitting elements of thebacklight 1160. For example, the BLC 1140 may include a pulse widthmodulation (PWM) driver (not shown) to generate a PWM signal thatactivates at least a portion of the light emitting elements of thebacklight 1160. The duty cycle and frequency of the PWM signal may causethe light generated by the light emitting elements to dim. For example,a 100% duty cycle may correspond to the light emitting elements beingfully on and a 0% duty cycle may correspond to the light emittingelements being fully off. Thus, intermediate duty cycles (e.g., 25%,50%) typically cause the light emitting elements to be turned on for aportion of a cycle period that is proportional to the percentage of theduty cycle. The cycle period of may be fast enough that the blinking ofthe light emitting elements is not noticeable to the human eye.Moreover, the effect to the user may be that the level of the lightemitted by the backlight 1160 is lower than if the backlight 1160 werefully activated. The BLC 1140 may be separate from or incorporated intothe TCON 1130.

Alternatively, an emissive display system may be used where the LCDpanel 1150 would be replaced by an emissive display panel (e.g. organiclight emitting diode/OLED) the backlight 1160 would be omitted, and therow and column drivers 1152 and 1154, respectively, may be used todirectly modulate pixel color and brightness.

Distance Based Display Resolution

FIG. 12A shows a scenario in which a user 1218 interacts with a dataprocessing device 1200 containing a display unit 1228. The displayprocessing device 1200 may include, for example, a notebook computer, adesktop computer, a tablet computer, a convertible tablet, a mobileInternet device (MID), a personal digital assistant (PDA), a wearabledevice (e.g., head mounted display/HMD), a media player, etc., or anycombination thereof. The illustrated data processing device 1200includes a processor 1224 (e.g., embedded controller, microcontroller,host processor, graphics processor) coupled to a memory 1222, which mayinclude storage locations that are addressable through the processor1224. As will be discussed in greater detail, a distance sensor 1210 mayenable distance based display resolution with respect to the displayunits 1228.

The illustrated memory 1222 includes display data 1226 that is to berendered on the display unit 1228. In one example, the processor 1224conducts data conversion on the display data 1226 prior to presentingthe display data 1226 on the display unit 1228. A post-processing engine1214 may execute on the processor 1224 to receive the display data 1226and an output of the distance sensor 1210. The post-processing engine1214 may modify the display data 1226 to enhance the readability ofscreen content on the display unit 1228, reduce power consumption in thedata processing device 1200, etc., or any combination thereof.

The illustrated memory 1222 stores a display resolution setting 1216, inaddition to an operating system 1212 and an application 1220. Thedisplay resolution setting 1216 may specify a number of pixels of thedisplay data 1226 to be presented on the display unit 1228 along alength dimension and a width dimension. If the display data 1226 asgenerated by the application 1220 is incompatible with the format of thedisplay unit 1228, the processor 1224 may configure the scale of thedisplay data 1226 to match the format of the display units 1228. In thisregard, the display resolution setting 1216 may be associated withand/or incorporated into configuration data that defines other settingsfor the display unit 1228. Moreover, the display resolution setting 1216may be defined in terms of unit distance or area (e.g., pixels perinch/PPI), or other suitable parameter.

The application 1220 may generate a user interface, wherein the user1218 may interact with the user interface to select the displayresolution setting 1216 from one or more options provided through theuser interface, enter the display resolution setting 1216 as a requestedvalue, and so forth. Thus, the display data 1226 may be resized to fitinto the display resolution setting 1216 prior to being rendered on thedisplay unit 1228.

The distance sensor 1210 may track the distance between the user 1218and the display unit 1228, wherein distance sensing may be triggeredthrough a physical button associated with the data processing device1200/display unit 1228, through the user interface provided by theapplication 1220 and/or loading of the operating system 1220, and soforth. For example, during a boot of the data processing device 1200 theoperating system 1212 may conduct an automatic process to trigger thedistance sensing in the background or foreground. Distance sensing maybe conducted periodically or continuously.

FIG. 12B shows one example of a distance sensing scenario. In theillustrated example, the distance sensor 1210 uses a transceiver 1208 toemit an electromagnetic beam 1202 in the direction of the user 1218.Thus, the transceiver 1202 might be positioned on a front facing surfaceof the data processing device 1200 (FIG. 12A). The electromagnetic beam1202 may impact the user 1218 and be reflected/scattered from the user1218 as a return electromagnetic beam 1204. The return electromagneticbeam 1204 may be analyzed by, for example, the processor 1224 (FIG. 12A)and/or the post-processing engine 1214 (FIG. 12A) to determine thedistance 1206 between the user 1218 and the display unit 1228 (FIG.12A). The distance 1206 may be used to adjust the display resolutionsetting 1216.

Display Layers

Turning now to FIG. 13, a display system 1300 is shown in which cascadeddisplay layers 1361, 1362 and 1363 are used to achieve spatial/temporalsuper-resolution in a display assembly 1360. In the illustrated example,a processor 1310 provides original graphics data 1334 (e.g., videoframes, still images), to the system 1300 via a bus 1320. A cascadeddisplay program 1331 may be stored in a memory 1330, wherein thecascaded display program 1331 may be part of a display driver associatedwith the display assembly 1360. The illustrated memory 1330 alsoincludes the original graphics data 1334 and factorized graphics data1335. In one example, the cascaded display program 1331 includes atemporal factorization component 1332 and a spatial factorizationcomponent 1333. The temporal factorization component 1332 may performtemporal factorization computation and the spatial factorizationcomponent may perform spatial factorization computation. The cascadeddisplay program 1331 may derive the factorized graphics data 1335 forpresentation on each display layer 1361, 1362 and 1363 based on userconfigurations and the original graphics data 1334.

The display assembly 1360 may be implemented as an LCD (liquid crystaldisplay) used in, for example, a head mounted display (HMD) application.More particularly, the display assembly 1360 may include a stack of LCDpanels interface boards a lens attachment, and so forth. Each panel maybe operated at a native resolution of, for example, 1280×800 pixels andwith a 60 Hz refresh rate. Other native resolutions, refresh rates,display panel technology and/or layer configurations may be used.

Multiple Display Units

FIG. 14 shows a graphics display system 1400 that includes a set ofdisplay units 1430 (1430 a-1430 n) that may generally be used to outputa widescreen (e.g., panoramic) presentation 1440 that includescoordinated content in a cohesive and structured topological form. Inthe illustrated example, a data processing device 1418 includes aprocessor 1415 that applies a logic function 1424 to hardware profiledata 1402 received from the set of display units 1430 over a network1420. The application of the logic function 1424 to the hardware profiledata 1402 may create a set of automatic topology settings 1406 when amatch of the hardware profile data with a set of settings in a hardwareprofile lookup table 1412 is not found. The illustrated set of automatictopology settings 1406 are transmitted from the display processingdevice 1418 to the display units 1430 over the network 1420.

The processor 1415 may perform and execute the logic function 1424 uponreceipt of the logic function 1424 from a display driver 1410. In thisregard, the display driver 1410 may include an auto topology module 1408that automatically configures and structures the topologies of thedisplay units 1432 to create the presentation 1440. In one example, thedisplay driver 1410 is a set of instructions, which when executed by theprocessor 1415, cause the data processing device 1418 to communicatewith the display units 1430, video cards, etc., and conduct automatictopology generation operations.

The data processing device 1418 may include, for example, a server,desktop, notebook computer, tablet computer, convertible tablet, MID,PDA, wearable device, media player, and so forth. Thus, the displayprocessing device 1418 may include a hardware control module 1416, astorage device 1414, random access memory (RAM, not shown), controllercards including one or more video controller cards, and so forth. In oneexample, the display units 1430 are flat-panel displays (e.g., liquidcrystal, active matrix, plasma, etc.), HMD's, video projection devices,and so forth, that coordinate with one another to produce thepresentation 1440. Moreover, the presentation 1440 may be generatedbased on a media file stored in the storage device 1414, wherein themedia file might include, for example, a film, video clip, animation,advertisement, etc., or any combination thereof.

The term “topology” may be considered the number, scaling, shape and/orother configuration parameter of a first display unit 1430 a, a seconddisplay unit 1430 b, a third display unit 1430 n, and so forth.Accordingly, the topology of the display units 1430 may enable thepresentation 1440 be visually presented in concert such that theindividual sections of the presentation 1440 are proportional andcompatible with the original dimensions and scope of the media beingplayed through the display units 1430. Thus, the topology may constitutespatial relations and/or geometric properties that are not impacted bythe continuous change of shape or size of the content rendered in thepresentation 1440. In one example, the auto topology module 1408includes a timing module 1426, a control module 1428, a signal monitormodule 1432 and a signal display module 1434. The timing module 1426 maydesignate a particular display unit in the set of display units 1430 asa sample display unit. In such a case, the timing module 1426 maydesignate the remaining display units 1430 as additional display units.In one example, the timing module 1426 automatically sets a shapingfactor to be compatible with the hardware profile data 1402, wherein thepresentation 1440 is automatically initiated by a sequence of graphicssignals 1422.

In one example, the control module 1428 modifies the set of automatictopology settings 1406. Additionally, the signal monitor module 1432 mayautomatically monitor the sequence of graphics signals 1422 and triggerthe storage device 1414 to associate the set of automatic topologysettings 1406 with the hardware profile lookup table 1412. Moreover, thesignal monitor module 1432 may automatically detect changes in the setof display units 1430 according to a set of change criteria andautomatically generate a new topology profile corresponding to thechange in the set of display units 1430. Thus, the new topology profilemay be applied to the set of display units 1430. The signal monitormodule 1432 may also trigger the signal display module 1434 to reapplythe set of automatic apology settings 1406 if the sequence of graphicssignals 1422 fails to meet a set of criteria. If the hardware profiledata 1402 does not support automatic topology display of the sequence ofgraphics signals 1422, the data processing device 1418 may report anerror and record the error in an error log 1413.

Cloud-Assisted Media Delivery

Turning now to FIG. 15, a cloud gaming system 1500 includes a client1540 that is coupled to a server 1520 through a network 1510. The client1540 may generally be a consumer of graphics (e.g., gaming, virtualreality/VR, augmented reality/AR) content that is housed, processed andrendered on the server 1520. The illustrated server 1520, which may bescalable, has the capacity to provide the graphics content to multipleclients simultaneously (e.g., by leveraging parallel and apportionedprocessing and rendering resources). In one example, the scalability ofthe server 1520 is limited by the capacity of the network 1510.Accordingly, there may be some threshold number of clients above whichthe service to all clients made degrade.

In one example, the server 1520 includes a graphics processor (e.g.,GPU) 1530, a host processor (e.g., CPU) 1524 and a network interfacecard (NIC) 1522. The NIC 1522 may receive a request from the client 1540for graphics content. The request from the client 1540 may cause thegraphics content to be retrieved from memory via an applicationexecuting on the host processor 1524. The host processor 1524 may carryout high level operations such as, for example, determining position,collision and motion of objects in a given scene. Based on the highlevel operations, the host processor 1524 may generate renderingcommands that are combined with the scene data and executed by thegraphics processor 1530. The rendering commands may cause the graphicsprocessor 1530 to define scene geometry, shading, lighting, motion,texturing, camera parameters, etc., for scenes to be presented via theclient 1540.

More particularly, the illustrated graphics processor 1530 includes agraphics renderer 1532 that executes rendering procedures according tothe rendering commands generated by the host processor 1524. The outputof the graphics renderer 1532 may be a stream of raw video frames thatare provided to a frame capturer 1534. The illustrated frame capturer1534 is coupled to an encoder 1536, which may compress/format the rawvideo stream for transmission over the network 1510. The encoder 1536may use a wide variety of video compression algorithms such as, forexample, the H.264 standard from the International TelecommunicationUnion Telecommunication Standardization Sector (ITUT), the MPEG4Advanced Video Coding (AVC) Standard from the International Organizationfor the Standardization/International Electrotechnical Commission(ISO/IEC), and so forth.

The illustrated client 1540, which may be a desktop computer, notebookcomputer, tablet computer, convertible tablet, wearable device, MID,PDA, media player, etc., includes an NIC 1542 to receive the transmittedvideo stream from the server 1520. The NIC 1522, may include thephysical layer and the basis for the software layer of the networkinterface in the client 1540 in order to facilitate communications overthe network 1510. The client 1540 may also include a decoder 1544 thatemploys the same formatting/compression scheme of the encoder 1536.Thus, the decompressed video stream may be provided from the decoder1544 to a video renderer 1546. The illustrated video renderer 1546 iscoupled to a display 1548 that visually presents the graphics content.

As already noted, the graphics content may include gaming content. Inthis regard, the client 1540 may conduct real-time interactive streamingthat involves the collection of user input from an input device 1550 anddelivery of the user input to the server 1520 via the network 1510. Thisreal-time interactive component of cloud gaming may pose challenges withregard to latency.

Additional System Overview Example

FIG. 16 is a block diagram of a processing system 1600, according to anembodiment. In various embodiments the system 1600 includes one or moreprocessors 1602 and one or more graphics processors 1608, and may be asingle processor desktop system, a multiprocessor workstation system, ora server system having a large number of processors 1602 or processorcores 1607. In one embodiment, the system 1600 is a processing platformincorporated within a system-on-a-chip (SoC) integrated circuit for usein mobile, handheld, or embedded devices.

In one embodiment the system 1600 can include, or be incorporated withina server-based gaming platform, a game console, including a game andmedia console, a mobile gaming console, a handheld game console, or anonline game console. In some embodiments the system 1600 is a mobilephone, smart phone, tablet computing device or mobile Internet device.The processing system 1600 can also include, couple with, or beintegrated within a wearable device, such as a smart watch wearabledevice, smart eyewear device, augmented reality device, or virtualreality device. In some embodiments, the processing system 1600 is atelevision or set top box device having one or more processors 1602 anda graphical interface generated by one or more graphics processors 1608.

In some embodiments, the one or more processors 1602 each include one ormore processor cores 1607 to process instructions which, when executed,perform operations for system and user software. In some embodiments,each of the one or more processor cores 1607 is configured to process aspecific instruction set 1609. In some embodiments, instruction set 1609may facilitate Complex Instruction Set Computing (CISC), ReducedInstruction Set Computing (RISC), or computing via a Very LongInstruction Word (VLIW). Multiple processor cores 1607 may each processa different instruction set 1609, which may include instructions tofacilitate the emulation of other instruction sets. Processor core 1607may also include other processing devices, such a Digital SignalProcessor (DSP).

In some embodiments, the processor 1602 includes cache memory 1604.Depending on the architecture, the processor 1602 can have a singleinternal cache or multiple levels of internal cache. In someembodiments, the cache memory is shared among various components of theprocessor 1602. In some embodiments, the processor 1602 also uses anexternal cache (e.g., a Level-3 (L3) cache or Last Level Cache (LLC))(not shown), which may be shared among processor cores 1607 using knowncache coherency techniques. A register file 1606 is additionallyincluded in processor 1602 which may include different types ofregisters for storing different types of data (e.g., integer registers,floating point registers, status registers, and an instruction pointerregister). Some registers may be general-purpose registers, while otherregisters may be specific to the design of the processor 1602.

In some embodiments, one or more processor(s) 1602 are coupled with oneor more interface bus(es) 1610 to transmit communication signals such asaddress, data, or control signals between processor 1602 and othercomponents in the system 1600. The interface bus 1610, in oneembodiment, can be a processor bus, such as a version of the DirectMedia Interface (DMI) bus. However, processor busses are not limited tothe DMI bus, and may include one or more Peripheral ComponentInterconnect buses (e.g., PCI, PCI Express), memory busses, or othertypes of interface busses. In one embodiment the processor(s) 1602include an integrated memory controller 1616 and a platform controllerhub 1630. The memory controller 1616 facilitates communication between amemory device and other components of the system 1600, while theplatform controller hub (PCH) 1630 provides connections to I/O devicesvia a local I/O bus.

The memory device 1620 can be a dynamic random access memory (DRAM)device, a static random access memory (SRAM) device, flash memorydevice, phase-change memory device, or some other memory device havingsuitable performance to serve as process memory. In one embodiment thememory device 1620 can operate as system memory for the system 1600, tostore data 1622 and instructions 1621 for use when the one or moreprocessors 1602 executes an application or process. Memory controller1616 also couples with an optional external graphics processor 1612,which may communicate with the one or more graphics processors 1608 inprocessors 1602 to perform graphics and media operations. In someembodiments a display device 1611 can connect to the processor(s) 1602.The display device 1611 can be one or more of an internal displaydevice, as in a mobile electronic device or a laptop device or anexternal display device attached via a display interface (e.g.,DisplayPort, etc.). In one embodiment the display device 1611 can be ahead mounted display (HMD) such as a stereoscopic display device for usein virtual reality (VR) applications or augmented reality (AR)applications.

In some embodiments the platform controller hub 1630 enables peripheralsto connect to memory device 1620 and processor 1602 via a high-speed I/Obus. The I/O peripherals include, but are not limited to, an audiocontroller 1646, a network controller 1634, a firmware interface 1628, awireless transceiver 1626, touch sensors 1625, a data storage device1624 (e.g., hard disk drive, flash memory, etc.). The data storagedevice 1624 can connect via a storage interface (e.g., SATA) or via aperipheral bus, such as a Peripheral Component Interconnect bus (e.g.,PCI, PCI Express). The touch sensors 1625 can include touch screensensors, pressure sensors, or fingerprint sensors. The wirelesstransceiver 1626 can be a Wi-Fi transceiver, a Bluetooth transceiver, ora mobile network transceiver such as a 3G, 4G, or Long Term Evolution(LTE) transceiver. The firmware interface 1628 enables communicationwith system firmware, and can be, for example, a unified extensiblefirmware interface (UEFI). The network controller 1634 can enable anetwork connection to a wired network. In some embodiments, ahigh-performance network controller (not shown) couples with theinterface bus 1610. The audio controller 1646, in one embodiment, is amulti-channel high definition audio controller. In one embodiment thesystem 1600 incudes an optional legacy I/O controller 1640 for couplinglegacy (e.g., Personal System 2 (PS/2)) devices to the system. Theplatform controller hub 1630 can also connect to one or more UniversalSerial Bus (USB) controllers 1642 connect input devices, such askeyboard and mouse 1643 combinations, a camera 1644, or other USB inputdevices.

It will be appreciated that the system 1600 shown is exemplary and notlimiting, as other types of data processing systems that are differentlyconfigured may also be used. For example, an instance of the memorycontroller 1616 and platform controller hub 1630 may be integrated intoa discreet external graphics processor, such as the external graphicsprocessor 1612. In one embodiment the platform controller hub 1630and/or memory controller 1660 may be external to the one or moreprocessor(s) 1602. For example, the system 1600 can include an externalmemory controller 1616 and platform controller hub 1630, which may beconfigured as a memory controller hub and peripheral controller hubwithin a system chipset that is in communication with the processor(s)1602.

FIG. 17 is a block diagram of an embodiment of a processor 1700 havingone or more processor cores 1702A-1702N, an integrated memory controller1714, and an integrated graphics processor 1708. Those elements of FIG.17 having the same reference numbers (or names) as the elements of anyother figure herein can operate or function in any manner similar tothat described elsewhere herein, but are not limited to such. Processor1700 can include additional cores up to and including additional core1702N represented by the dashed lined boxes. Each of processor cores1702A-1702N includes one or more internal cache units 1704A-1704N. Insome embodiments each processor core also has access to one or moreshared cached units 1706.

The internal cache units 1704A-1704N and shared cache units 1706represent a cache memory hierarchy within the processor 1700. The cachememory hierarchy may include at least one level of instruction and datacache within each processor core and one or more levels of sharedmid-level cache, such as a Level 2 (L2), Level 3 (L3), Level 4 (L4), orother levels of cache, where the highest level of cache before externalmemory is classified as the LLC. In some embodiments, cache coherencylogic maintains coherency between the various cache units 1706 and1704A-1704N.

In some embodiments, processor 1700 may also include a set of one ormore bus controller units 1716 and a system agent core 1710. The one ormore bus controller units 1716 manage a set of peripheral buses, such asone or more PCI or PCI express busses. System agent core 1710 providesmanagement functionality for the various processor components. In someembodiments, system agent core 1710 includes one or more integratedmemory controllers 1714 to manage access to various external memorydevices (not shown).

In some embodiments, one or more of the processor cores 1702A-1702Ninclude support for simultaneous multi-threading. In such embodiment,the system agent core 1710 includes components for coordinating andoperating cores 1702A-1702N during multi-threaded processing. Systemagent core 1710 may additionally include a power control unit (PCU),which includes logic and components to regulate the power state ofprocessor cores 1702A-1702N and graphics processor 1708.

In some embodiments, processor 1700 additionally includes graphicsprocessor 1708 to execute graphics processing operations. In someembodiments, the graphics processor 1708 couples with the set of sharedcache units 1706, and the system agent core 1710, including the one ormore integrated memory controllers 1714. In some embodiments, the systemagent core 1710 also includes a display controller 1711 to drivegraphics processor output to one or more coupled displays. In someembodiments, display controller 1711 may also be a separate modulecoupled with the graphics processor via at least one interconnect, ormay be integrated within the graphics processor 1708.

In some embodiments, a ring based interconnect unit 1712 is used tocouple the internal components of the processor 1700. However, analternative interconnect unit may be used, such as a point-to-pointinterconnect, a switched interconnect, or other techniques, includingtechniques well known in the art. In some embodiments, graphicsprocessor 1708 couples with the ring interconnect 1712 via an I/O link1713.

The exemplary I/O link 1713 represents at least one of multiplevarieties of I/O interconnects, including an on package I/O interconnectwhich facilitates communication between various processor components anda high-performance embedded memory module 1718, such as an eDRAM module.In some embodiments, each of the processor cores 1702A-1702N andgraphics processor 1708 use embedded memory modules 1718 as a sharedLast Level Cache.

In some embodiments, processor cores 1702A-1702N are homogenous coresexecuting the same instruction set architecture. In another embodiment,processor cores 1702A-1702N are heterogeneous in terms of instructionset architecture (ISA), where one or more of processor cores 1702A-1702Nexecute a first instruction set, while at least one of the other coresexecutes a subset of the first instruction set or a differentinstruction set. In one embodiment processor cores 1702A-1702N areheterogeneous in terms of microarchitecture, where one or more coreshaving a relatively higher power consumption couple with one or morepower cores having a lower power consumption. Additionally, processor1700 can be implemented on one or more chips or as an SoC integratedcircuit having the illustrated components, in addition to othercomponents.

FIG. 18 is a block diagram of a graphics processor 1800, which may be adiscrete graphics processing unit, or may be a graphics processorintegrated with a plurality of processing cores. In some embodiments,the graphics processor communicates via a memory mapped I/O interface toregisters on the graphics processor and with commands placed into theprocessor memory. In some embodiments, graphics processor 1800 includesa memory interface 1814 to access memory. Memory interface 1814 can bean interface to local memory, one or more internal caches, one or moreshared external caches, and/or to system memory.

In some embodiments, graphics processor 1800 also includes a displaycontroller 1802 to drive display output data to a display device 1820.Display controller 1802 includes hardware for one or more overlay planesfor the display and composition of multiple layers of video or userinterface elements. The display device 1820 can be an internal orexternal display device. In one embodiment the display device 1820 is ahead mounted display device, such as a virtual reality (VR) displaydevice or an augmented reality (AR) display device. In some embodiments,graphics processor 1800 includes a video codec engine 1806 to encode,decode, or transcode media to, from, or between one or more mediaencoding formats, including, but not limited to Moving Picture ExpertsGroup (MPEG) formats such as MPEG-2, Advanced Video Coding (AVC) formatssuch as H.264/MPEG-4 AVC, as well as the Society of Motion Picture &Television Engineers (SMPTE) 421M/VC-1, and Joint Photographic ExpertsGroup (JPEG) formats such as JPEG, and Motion JPEG (MJPEG) formats.

In some embodiments, graphics processor 1800 includes a block imagetransfer (BLIT) engine 1804 to perform two-dimensional (2D) rasterizeroperations including, for example, bit-boundary block transfers.However, in one embodiment, 2D graphics operations are performed usingone or more components of graphics processing engine (GPE) 1810. In someembodiments, GPE 1810 is a compute engine for performing graphicsoperations, including three-dimensional (3D) graphics operations andmedia operations.

In some embodiments, GPE 1810 includes a 18D pipeline 1812 forperforming 3D operations, such as rendering three-dimensional images andscenes using processing functions that act upon 3D primitive shapes(e.g., rectangle, triangle, etc.). The 3D pipeline 1812 includesprogrammable and fixed function elements that perform various taskswithin the element and/or spawn execution threads to a 3D/Mediasub-system 1815. While 3D pipeline 1812 can be used to perform mediaoperations, an embodiment of GPE 1810 also includes a media pipeline1816 that is specifically used to perform media operations, such asvideo post-processing and image enhancement.

In some embodiments, media pipeline 1816 includes fixed function orprogrammable logic units to perform one or more specialized mediaoperations, such as video decode acceleration, video de-interlacing, andvideo encode acceleration in place of, or on behalf of video codecengine 1806. In some embodiments, media pipeline 1816 additionallyincludes a thread spawning unit to spawn threads for execution on3D/Media sub-system 1815. The spawned threads perform computations forthe media operations on one or more graphics execution units included in3D/Media sub-system 1815.

In some embodiments, 3D/Media subsystem 1815 includes logic forexecuting threads spawned by 3D pipeline 1812 and media pipeline 1816.In one embodiment, the pipelines send thread execution requests to3D/Media subsystem 1815, which includes thread dispatch logic forarbitrating and dispatching the various requests to available threadexecution resources. The execution resources include an array ofgraphics execution units to process the 3D and media threads. In someembodiments, 3D/Media subsystem 1815 includes one or more internalcaches for thread instructions and data. In some embodiments, thesubsystem also includes shared memory, including registers andaddressable memory, to share data between threads and to store outputdata.

Graphics Processing Engine

FIG. 19 is a block diagram of a graphics processing engine 1910 of agraphics processor in accordance with some embodiments. In oneembodiment, the graphics processing engine (GPE) 1910 is a version ofthe GPE 1810 shown in FIG. 18. Elements of FIG. 19 having the samereference numbers (or names) as the elements of any other figure hereincan operate or function in any manner similar to that describedelsewhere herein, but are not limited to such. For example, the 3Dpipeline 1812 and media pipeline 1816 of FIG. 18 are illustrated. Themedia pipeline 1816 is optional in some embodiments of the GPE 1910 andmay not be explicitly included within the GPE 1910. For example and inat least one embodiment, a separate media and/or image processor iscoupled to the GPE 1910.

In some embodiments, GPE 1910 couples with or includes a commandstreamer 1903, which provides a command stream to the 3D pipeline 1812and/or media pipelines 1816. In some embodiments, command streamer 1903is coupled with memory, which can be system memory, or one or more ofinternal cache memory and shared cache memory. In some embodiments,command streamer 1903 receives commands from the memory and sends thecommands to 3D pipeline 1812 and/or media pipeline 1816. The commandsare directives fetched from a ring buffer, which stores commands for the3D pipeline 1812 and media pipeline 1816. In one embodiment, the ringbuffer can additionally include batch command buffers storing batches ofmultiple commands. The commands for the 3D pipeline 1812 can alsoinclude references to data stored in memory, such as but not limited tovertex and geometry data for the 3D pipeline 1812 and/or image data andmemory objects for the media pipeline 1816. The 3D pipeline 1812 andmedia pipeline 1816 process the commands and data by performingoperations via logic within the respective pipelines or by dispatchingone or more execution threads to a graphics core array 1914. In oneembodiment the graphics core array 1914 include one or more blocks ofgraphics cores (e.g., graphics core(s) 1915A, graphics core(s) 1915B),each block including one or more graphics cores. Each graphics coreincludes a set of graphics execution resources that includesgeneral-purpose and graphics specific execution logic to performgraphics and compute operations, as well as fixed function textureprocessing and/or machine learning and artificial intelligenceacceleration logic.

In various embodiments the 3D pipeline 1812 includes fixed function andprogrammable logic to process one or more shader programs, such asvertex shaders, geometry shaders, pixel shaders, fragment shaders,compute shaders, or other shader programs, by processing theinstructions and dispatching execution threads to the graphics corearray 1914. The graphics core array 1914 provides a unified block ofexecution resources for use in processing these shader programs.Multi-purpose execution logic (e.g., execution units) within thegraphics core(s) 1915A-1914B of the graphic core array 1914 includessupport for various 3D API shader languages and can execute multiplesimultaneous execution threads associated with multiple shaders.

In some embodiments the graphics core array 1914 also includes executionlogic to perform media functions, such as video and/or image processing.In one embodiment, the execution units additionally includegeneral-purpose logic that is programmable to perform parallelgeneral-purpose computational operations, in addition to graphicsprocessing operations. The general-purpose logic can perform processingoperations in parallel or in conjunction with general-purpose logicwithin the processor core(s) 107 of FIG. 1 or core 202A-1702N as in FIG.2.

Output data generated by threads executing on the graphics core array1914 can output data to memory in a unified return buffer (URB) 1918.The URB 1918 can store data for multiple threads. In some embodimentsthe URB 1918 may be used to send data between different threadsexecuting on the graphics core array 1914. In some embodiments the URB1918 may additionally be used for synchronization between threads on thegraphics core array and fixed function logic within the shared functionlogic 1920.

In some embodiments, graphics core array 1914 is scalable, such that thearray includes a variable number of graphics cores, each having avariable number of execution units based on the target power andperformance level of GPE 1910. In one embodiment the execution resourcesare dynamically scalable, such that execution resources may be enabledor disabled as needed.

The graphics core array 1914 couples with shared function logic 1920that includes multiple resources that are shared between the graphicscores in the graphics core array. The shared functions within the sharedfunction logic 1920 are hardware logic units that provide specializedsupplemental functionality to the graphics core array 1914. In variousembodiments, shared function logic 1920 includes but is not limited tosampler 1921, math 1922, and inter-thread communication (ITC) 1923logic. Additionally, some embodiments implement one or more cache(s)1925 within the shared function logic 1920.

A shared function is implemented where the demand for a givenspecialized function is insufficient for inclusion within the graphicscore array 1914. Instead a single instantiation of that specializedfunction is implemented as a stand-alone entity in the shared functionlogic 1920 and shared among the execution resources within the graphicscore array 1914. The precise set of functions that are shared betweenthe graphics core array 1914 and included within the graphics core array1914 varies across embodiments. In some embodiments, specific sharedfunctions within the shared function logic 1920 that are usedextensively by the graphics core array 1914 may be included withinshared function logic 1916 within the graphics core array 1914. Invarious embodiments, the shared function logic 1916 within the graphicscore array 1914 can include some or all logic within the shared functionlogic 1920. In one embodiment, all logic elements within the sharedfunction logic 1920 may be duplicated within the shared function logic1916 of the graphics core array 1914. In one embodiment the sharedfunction logic 1920 is excluded in favor of the shared function logic1916 within the graphics core array 1914.

FIG. 20 is a block diagram of hardware logic of a graphics processorcore 2000, according to some embodiments described herein. Elements ofFIG. 20 having the same reference numbers (or names) as the elements ofany other figure herein can operate or function in any manner similar tothat described elsewhere herein, but are not limited to such. Theillustrated graphics processor core 2000, in some embodiments, isincluded within the graphics core array 1914 of FIG. 19. The graphicsprocessor core 2000, sometimes referred to as a core slice, can be oneor multiple graphics cores within a modular graphics processor. Thegraphics processor core 2000 is exemplary of one graphics core slice,and a graphics processor as described herein may include multiplegraphics core slices based on target power and performance envelopes.Each graphics core 2000 can include a fixed function block 2030 coupledwith multiple sub-cores 2001A-2001F, also referred to as sub-slices,that include modular blocks of general-purpose and fixed function logic.

In some embodiments the fixed function block 2030 includes ageometry/fixed function pipeline 2036 that can be shared by allsub-cores in the graphics processor 2000, for example, in lowerperformance and/or lower power graphics processor implementations. Invarious embodiments, the geometry/fixed function pipeline 2036 includesa 3D fixed function pipeline (e.g., 3D pipeline 1812 as in FIG. 18 andFIG. 19) a video front-end unit, a thread spawner and thread dispatcher,and a unified return buffer manager, which manages unified returnbuffers, such as the unified return buffer 1918 of FIG. 19.

In one embodiment the fixed function block 2030 also includes a graphicsSoC interface 2037, a graphics microcontroller 2038, and a mediapipeline 2039. The graphics SoC interface 2037 provides an interfacebetween the graphics core 2000 and other processor cores within a systemon a chip integrated circuit. The graphics microcontroller 2038 is aprogrammable sub-processor that is configurable to manage variousfunctions of the graphics processor 2000, including thread dispatch,scheduling, and pre-emption. The media pipeline 2039 (e.g., mediapipeline 1816 of FIG. 18 and FIG. 19) includes logic to facilitate thedecoding, encoding, pre-processing, and/or post-processing of multimediadata, including image and video data. The media pipeline 2039 implementmedia operations via requests to compute or sampling logic within thesub-cores 2001-2001F.

In one embodiment the SoC interface 2037 enables the graphics core 2000to communicate with general-purpose application processor cores (e.g.,CPUs) and/or other components within an SoC, including memory hierarchyelements such as a shared last level cache memory, the system RAM,and/or embedded on-chip or on-package DRAM. The SoC interface 2037 canalso enable communication with fixed function devices within the SoC,such as camera imaging pipelines, and enables the use of and/orimplements global memory atomics that may be shared between the graphicscore 2000 and CPUs within the SoC. The SoC interface 2037 can alsoimplement power management controls for the graphics core 2000 andenable an interface between a clock domain of the graphic core 2000 andother clock domains within the SoC. In one embodiment the SoC interface2037 enables receipt of command buffers from a command streamer andglobal thread dispatcher that are configured to provide commands andinstructions to each of one or more graphics cores within a graphicsprocessor. The commands and instructions can be dispatched to the mediapipeline 2039, when media operations are to be performed, or a geometryand fixed function pipeline (e.g., geometry and fixed function pipeline2036, geometry and fixed function pipeline 2014) when graphicsprocessing operations are to be performed.

The graphics microcontroller 2038 can be configured to perform variousscheduling and management tasks for the graphics core 2000. In oneembodiment the graphics microcontroller 2038 can perform graphics and/orcompute workload scheduling on the various graphics parallel engineswithin execution unit (EU) arrays 2002A-2002F, 2004A-2004F within thesub-cores 2001A-2001F. In this scheduling model, host software executingon a CPU core of an SoC including the graphics core 2000 can submitworkloads one of multiple graphic processor doorbells, which invokes ascheduling operation on the appropriate graphics engine. Schedulingoperations include determining which workload to run next, submitting aworkload to a command streamer, pre-empting existing workloads runningon an engine, monitoring progress of a workload, and notifying hostsoftware when a workload is complete. In one embodiment the graphicsmicrocontroller 2038 can also facilitate low-power or idle states forthe graphics core 2000, providing the graphics core 2000 with theability to save and restore registers within the graphics core 2000across low-power state transitions independently from the operatingsystem and/or graphics driver software on the system.

The graphics core 2000 may have greater than or fewer than theillustrated sub-cores 2001A-2001F, up to N modular sub-cores. For eachset of N sub-cores, the graphics core 2000 can also include sharedfunction logic 2010, shared and/or cache memory 2012, a geometry/fixedfunction pipeline 2014, as well as additional fixed function logic 2016to accelerate various graphics and compute processing operations. Theshared function logic 2010 can include logic units associated with theshared function logic 1920 of FIG. 19 (e.g., sampler, math, and/orinter-thread communication logic) that can be shared by each N sub-coreswithin the graphics core 2000. The shared and/or cache memory 2012 canbe a last-level cache for the set of N sub-cores 2001A-2001F within thegraphics core 2000, and can also serve as shared memory that isaccessible by multiple sub-cores. The geometry/fixed function pipeline2014 can be included instead of the geometry/fixed function pipeline2036 within the fixed function block 2030 and can include the same orsimilar logic units.

In one embodiment the graphics core 2000 includes additional fixedfunction logic 2016 that can include various fixed function accelerationlogic for use by the graphics core 2000. In one embodiment theadditional fixed function logic 2016 includes an additional geometrypipeline for use in position only shading. In position-only shading, twogeometry pipelines exist, the full geometry pipeline within thegeometry/fixed function pipeline 2016, 2036, and a cull pipeline, whichis an additional geometry pipeline which may be included within theadditional fixed function logic 2016. In one embodiment the cullpipeline is a trimmed down version of the full geometry pipeline. Thefull pipeline and the cull pipeline can execute different instances ofthe same application, each instance having a separate context. Positiononly shading can hide long cull runs of discarded triangles, enablingshading to be completed earlier in some instances. For example and inone embodiment the cull pipeline logic within the additional fixedfunction logic 2016 can execute position shaders in parallel with themain application and generally generates critical results faster thanthe full pipeline, as the cull pipeline fetches and shades only theposition attribute of the vertices, without performing rasterization andrendering of the pixels to the frame buffer. The cull pipeline can usethe generated critical results to compute visibility information for allthe triangles without regard to whether those triangles are culled. Thefull pipeline (which in this instance may be referred to as a replaypipeline) can consume the visibility information to skip the culledtriangles to shade only the visible triangles that are finally passed tothe rasterization phase.

In one embodiment the additional fixed function logic 2016 can alsoinclude machine-learning acceleration logic, such as fixed functionmatrix multiplication logic, for implementations including optimizationsfor machine learning training or inferencing.

Within each graphics sub-core 2001A-2001F includes a set of executionresources that may be used to perform graphics, media, and computeoperations in response to requests by graphics pipeline, media pipeline,or shader programs. The graphics sub-cores 2001A-2001F include multipleEU arrays 2002A-2002F, 2004A-2004F, thread dispatch and inter-threadcommunication (TD/IC) logic 2003A-2003F, a 3D (e.g., texture) sampler2005A-2005F, a media sampler 2006A-2006F, a shader processor2007A-2007F, and shared local memory (SLM) 2008A-2008F. The EU arrays2002A-2002F, 2004A-2004F each include multiple execution units, whichare general-purpose graphics processing units capable of performingfloating-point and integer/fixed-point logic operations in service of agraphics, media, or compute operation, including graphics, media, orcompute shader programs. The TD/IC logic 2003A-2003F performs localthread dispatch and thread control operations for the execution unitswithin a sub-core and facilitate communication between threads executingon the execution units of the sub-core. The 3D sampler 2005A-2005F canread texture or other 3D graphics related data into memory. The 3Dsampler can read texture data differently based on a configured samplestate and the texture format associated with a given texture. The mediasampler 2006A-2006F can perform similar read operations based on thetype and format associated with media data. In one embodiment, eachgraphics sub-core 2001A-2001F can alternately include a unified 3D andmedia sampler. Threads executing on the execution units within each ofthe sub-cores 2001A-2001F can make use of shared local memory2008A-2008F within each sub-core, to enable threads executing within athread group to execute using a common pool of on-chip memory.

Execution Units

FIGS. 21A-21B illustrate thread execution logic 2100 including an arrayof processing elements employed in a graphics processor core accordingto embodiments described herein. Elements of FIGS. 21A-21B having thesame reference numbers (or names) as the elements of any other figureherein can operate or function in any manner similar to that describedelsewhere herein, but are not limited to such. FIG. 21A illustrates anoverview of thread execution logic 2100, which can include a variant ofthe hardware logic illustrated with each sub-core 2001A-2001F of FIG.20. FIG. 21B illustrates exemplary internal details of an executionunit.

As illustrated in FIG. 21A, in some embodiments thread execution logic2100 includes a shader processor 2102, a thread dispatcher 2104,instruction cache 2106, a scalable execution unit array including aplurality of execution units 2108A-2108N, a sampler 2110, a data cache2112, and a data port 2114. In one embodiment the scalable executionunit array can dynamically scale by enabling or disabling one or moreexecution units (e.g., any of execution unit 2108A, 2108B, 2108C, 2108D,through 2108N-1 and 2108N) based on the computational requirements of aworkload. In one embodiment the included components are interconnectedvia an interconnect fabric that links to each of the components. In someembodiments, thread execution logic 2100 includes one or moreconnections to memory, such as system memory or cache memory, throughone or more of instruction cache 2106, data port 2114, sampler 2110, andexecution units 2108A-2108N. In some embodiments, each execution unit(e.g. 2108A) is a stand-alone programmable general-purpose computationalunit that is capable of executing multiple simultaneous hardware threadswhile processing multiple data elements in parallel for each thread. Invarious embodiments, the array of execution units 2108A-2108N isscalable to include any number individual execution units.

In some embodiments, the execution units 2108A-2108N are primarily usedto execute shader programs. A shader processor 2102 can process thevarious shader programs and dispatch execution threads associated withthe shader programs via a thread dispatcher 2104. In one embodiment thethread dispatcher includes logic to arbitrate thread initiation requestsfrom the graphics and media pipelines and instantiate the requestedthreads on one or more execution unit in the execution units2108A-2108N. For example, a geometry pipeline can dispatch vertex,tessellation, or geometry shaders to the thread execution logic forprocessing. In some embodiments, thread dispatcher 2104 can also processruntime thread spawning requests from the executing shader programs.

In some embodiments, the execution units 2108A-2108N support aninstruction set that includes native support for many standard 3Dgraphics shader instructions, such that shader programs from graphicslibraries (e.g., Direct 3D and OpenGL) are executed with a minimaltranslation. The execution units support vertex and geometry processing(e.g., vertex programs, geometry programs, vertex shaders), pixelprocessing (e.g., pixel shaders, fragment shaders) and general-purposeprocessing (e.g., compute and media shaders). Each of the executionunits 2108A-2108N is capable of multi-issue single instruction multipledata (SIMD) execution and multi-threaded operation enables an efficientexecution environment in the face of higher latency memory accesses.Each hardware thread within each execution unit has a dedicatedhigh-bandwidth register file and associated independent thread-state.Execution is multi-issue per clock to pipelines capable of integer,single and double precision floating point operations, SIMD branchcapability, logical operations, transcendental operations, and othermiscellaneous operations. While waiting for data from memory or one ofthe shared functions, dependency logic within the execution units2108A-2108N causes a waiting thread to sleep until the requested datahas been returned. While the waiting thread is sleeping, hardwareresources may be devoted to processing other threads. For example,during a delay associated with a vertex shader operation, an executionunit can perform operations for a pixel shader, fragment shader, oranother type of shader program, including a different vertex shader.

Each execution unit in execution units 2108A-2108N operates on arrays ofdata elements. The number of data elements is the “execution size,” orthe number of channels for the instruction. An execution channel is alogical unit of execution for data element access, masking, and flowcontrol within instructions. The number of channels may be independentof the number of physical Arithmetic Logic Units (ALUs) or FloatingPoint Units (FPUs) for a particular graphics processor. In someembodiments, execution units 2108A-2108N support integer andfloating-point data types.

The execution unit instruction set includes SIMD instructions. Thevarious data elements can be stored as a packed data type in a registerand the execution unit will process the various elements based on thedata size of the elements. For example, when operating on a 256-bit widevector, the 256 bits of the vector are stored in a register and theexecution unit operates on the vector as four separate 64-bit packeddata elements (Quad-Word (QW) size data elements), eight separate 32-bitpacked data elements (Double Word (DW) size data elements), sixteenseparate 16-bit packed data elements (Word (W) size data elements), orthirty-two separate 8-bit data elements (byte (B) size data elements).However, different vector widths and register sizes are possible.

In one embodiment one or more execution units can be combined into afused execution unit 2109A-2109N having thread control logic(607A-2107N) that is common to the fused EUs. Multiple EUs can be fusedinto an EU group. Each EU in the fused EU group can be configured toexecute a separate SIMD hardware thread. The number of EUs in a fused EUgroup can vary according to embodiments. Additionally, various SIMDwidths can be performed per-EU, including but not limited to SIMD8,SIMD16, and SIMD32. Each fused graphics execution unit 2109A-2109Nincludes at least two execution units. For example, fused execution unit2109A includes a first EU 2108A, second EU 2108B, and thread controllogic 2107A that is common to the first EU 2108A and the second EU2108B. The thread control logic 2107A controls threads executed on thefused graphics execution unit 2109A, allowing each EU within the fusedexecution units 2109A-2109N to execute using a common instructionpointer register.

One or more internal instruction caches (e.g., 2106) are included in thethread execution logic 2100 to cache thread instructions for theexecution units. In some embodiments, one or more data caches (e.g.,2112) are included to cache thread data during thread execution. In someembodiments, a sampler 2110 is included to provide texture sampling for3D operations and media sampling for media operations. In someembodiments, sampler 2110 includes specialized texture or media samplingfunctionality to process texture or media data during the samplingprocess before providing the sampled data to an execution unit.

During execution, the graphics and media pipelines send threadinitiation requests to thread execution logic 2100 via thread spawningand dispatch logic. Once a group of geometric objects has been processedand rasterized into pixel data, pixel processor logic (e.g., pixelshader logic, fragment shader logic, etc.) within the shader processor2102 is invoked to further compute output information and cause resultsto be written to output surfaces (e.g., color buffers, depth buffers,stencil buffers, etc.). In some embodiments, a pixel shader or fragmentshader calculates the values of the various vertex attributes that areto be interpolated across the rasterized object. In some embodiments,pixel processor logic within the shader processor 2102 then executes anapplication programming interface (API)-supplied pixel or fragmentshader program. To execute the shader program, the shader processor 2102dispatches threads to an execution unit (e.g., 2108A) via threaddispatcher 2104. In some embodiments, shader processor 2102 uses texturesampling logic in the sampler 2110 to access texture data in texturemaps stored in memory. Arithmetic operations on the texture data and theinput geometry data compute pixel color data for each geometricfragment, or discards one or more pixels from further processing.

In some embodiments, the data port 2114 provides a memory accessmechanism for the thread execution logic 2100 to output processed datato memory for further processing on a graphics processor outputpipeline. In some embodiments, the data port 2114 includes or couples toone or more cache memories (e.g., data cache 2112) to cache data formemory access via the data port.

As illustrated in FIG. 21B, a graphics execution unit 2108 can includean instruction fetch unit 2137, a general register file array (GRF)2124, an architectural register file array (ARF) 2126, a thread arbiter2122, a send unit 2130, a branch unit 2132, a set of SIMD floating pointunits (FPUs) 2134, and in one embodiment a set of dedicated integer SIMDALUs 2135. The GRF 2124 and ARF 2126 includes the set of generalregister files and architecture register files associated with eachsimultaneous hardware thread that may be active in the graphicsexecution unit 2108. In one embodiment, per thread architectural stateis maintained in the ARF 2126, while data used during thread executionis stored in the GRF 2124. The execution state of each thread, includingthe instruction pointers for each thread, can be held in thread-specificregisters in the ARF 2126.

In one embodiment the graphics execution unit 2108 has an architecturethat is a combination of Simultaneous Multi-Threading (SMT) andfine-grained Interleaved Multi-Threading (IMT). The architecture has amodular configuration that can be fine tuned at design time based on atarget number of simultaneous threads and number of registers perexecution unit, where execution unit resources are divided across logicused to execute multiple simultaneous threads.

In one embodiment, the graphics execution unit 2108 can co-issuemultiple instructions, which may each be different instructions. Thethread arbiter 2122 of the graphics execution unit thread 2108 candispatch the instructions to one of the send unit 2130, branch unit2142, or SIMD FPU(s) 2134 for execution. Each execution thread canaccess 128 general-purpose registers within the GRF 2124, where eachregister can store 32 bytes, accessible as a SIMD 8-element vector of32-bit data elements. In one embodiment, each execution unit thread hasaccess to 4 Kbytes within the GRF 2124, although embodiments are not solimited, and greater or fewer register resources may be provided inother embodiments. In one embodiment up to seven threads can executesimultaneously, although the number of threads per execution unit canalso vary according to embodiments. In an embodiment in which seventhreads may access 4 Kbytes, the GRF 2124 can store a total of 28Kbytes. Flexible addressing modes can permit registers to be addressedtogether to build effectively wider registers or to represent stridedrectangular block data structures.

In one embodiment, memory operations, sampler operations, and otherlonger-latency system communications are dispatched via “send”instructions that are executed by the message passing send unit 2130. Inone embodiment, branch instructions are dispatched to a dedicated branchunit 2132 to facilitate SIMD divergence and eventual convergence.

In one embodiment the graphics execution unit 2108 includes one or moreSIMD floating point units (FPU(s)) 2134 to perform floating-pointoperations. In one embodiment, the FPU(s) 2134 also support integercomputation. In one embodiment the FPU(s) 2134 can SIMD execute up to Mnumber of 32-bit floating-point (or integer) operations, or SIMD executeup to 2M 16-bit integer or 16-bit floating-point operations. In oneembodiment, at least one of the FPU(s) provides extended math capabilityto support high-throughput transcendental math functions and doubleprecision 64-bit floating-point. In some embodiments, a set of 8-bitinteger SIMD ALUs 2135 are also present, and may be specificallyoptimized to perform operations associated with machine learningcomputations.

In one embodiment, arrays of multiple instances of the graphicsexecution unit 2108 can be instantiated in a graphics sub-core grouping(e.g., a sub-slice). For scalability, product architects can chose theexact number of execution units per sub-core grouping. In one embodimentthe execution unit 2108 can execute instructions across a plurality ofexecution channels. In a further embodiment, each thread executed on thegraphics execution unit 2108 is executed on a different channel.

FIG. 22 is a block diagram illustrating a graphics processor instructionformats 2200 according to some embodiments. In one or more embodiment,the graphics processor execution units support an instruction set havinginstructions in multiple formats. The solid lined boxes illustrate thecomponents that are generally included in an execution unit instruction,while the dashed lines include components that are optional or that areonly included in a sub-set of the instructions. In some embodiments,instruction format 2200 described and illustrated aremacro-instructions, in that they are instructions supplied to theexecution unit, as opposed to micro-operations resulting frominstruction decode once the instruction is processed.

In some embodiments, the graphics processor execution units nativelysupport instructions in a 128-bit instruction format 2210. A 64-bitcompacted instruction format 2230 is available for some instructionsbased on the selected instruction, instruction options, and number ofoperands. The native 128-bit instruction format 2210 provides access toall instruction options, while some options and operations arerestricted in the 64-bit format 2230. The native instructions availablein the 64-bit format 2230 vary by embodiment. In some embodiments, theinstruction is compacted in part using a set of index values in an indexfield 2213. The execution unit hardware references a set of compactiontables based on the index values and uses the compaction table outputsto reconstruct a native instruction in the 128-bit instruction format2210.

For each format, instruction opcode 2212 defines the operation that theexecution unit is to perform. The execution units execute eachinstruction in parallel across the multiple data elements of eachoperand. For example, in response to an add instruction the executionunit performs a simultaneous add operation across each color channelrepresenting a texture element or picture element. By default, theexecution unit performs each instruction across all data channels of theoperands. In some embodiments, instruction control field 2214 enablescontrol over certain execution options, such as channels selection(e.g., predication) and data channel order (e.g., swizzle). Forinstructions in the 128-bit instruction format 2210 an exec-size field2216 limits the number of data channels that will be executed inparallel. In some embodiments, exec-size field 2216 is not available foruse in the 64-bit compact instruction format 2230.

Some execution unit instructions have up to three operands including twosource operands, src0 2220, src1 2222, and one destination 2218. In someembodiments, the execution units support dual destination instructions,where one of the destinations is implied. Data manipulation instructionscan have a third source operand (e.g., SRC2 2224), where the instructionopcode 2212 determines the number of source operands. An instruction'slast source operand can be an immediate (e.g., hard-coded) value passedwith the instruction.

In some embodiments, the 128-bit instruction format 2210 includes anaccess/address mode field 2226 specifying, for example, whether directregister addressing mode or indirect register addressing mode is used.When direct register addressing mode is used, the register address ofone or more operands is directly provided by bits in the instruction.

In some embodiments, the 128-bit instruction format 2210 includes anaccess/address mode field 2226, which specifies an address mode and/oran access mode for the instruction. In one embodiment the access mode isused to define a data access alignment for the instruction. Someembodiments support access modes including a 16-byte aligned access modeand a 1-byte aligned access mode, where the byte alignment of the accessmode determines the access alignment of the instruction operands. Forexample, when in a first mode, the instruction may use byte-alignedaddressing for source and destination operands and when in a secondmode, the instruction may use 16-byte-aligned addressing for all sourceand destination operands.

In one embodiment, the address mode portion of the access/address modefield 2226 determines whether the instruction is to use direct orindirect addressing. When direct register addressing mode is used bitsin the instruction directly provide the register address of one or moreoperands. When indirect register addressing mode is used, the registeraddress of one or more operands may be computed based on an addressregister value and an address immediate field in the instruction.

In some embodiments instructions are grouped based on opcode 2212bit-fields to simplify Opcode decode 2240. For an 8-bit opcode, bits 4,5, and 6 allow the execution unit to determine the type of opcode. Theprecise opcode grouping shown is merely an example. In some embodiments,a move and logic opcode group 2242 includes data movement and logicinstructions (e.g., move (mov), compare (cmp)). In some embodiments,move and logic group 2242 shares the five most significant bits (MSB),where move (mov) instructions are in the form of 0000xxxxb and logicinstructions are in the form of 0001xxxxb. A flow control instructiongroup 2244 (e.g., call, jump (jmp)) includes instructions in the form of0010xxxxb (e.g., 0x20). A miscellaneous instruction group 2246 includesa mix of instructions, including synchronization instructions (e.g.,wait, send) in the form of 0011xxxxb (e.g., 0x30). A parallel mathinstruction group 2248 includes component-wise arithmetic instructions(e.g., add, multiply (mul)) in the form of 0100xxxxb (e.g., 0x40). Theparallel math group 2248 performs the arithmetic operations in parallelacross data channels. The vector math group 2250 includes arithmeticinstructions (e.g., dp4) in the form of 0101xxxxb (e.g., 0x50). Thevector math group performs arithmetic such as dot product calculationson vector operands.

Graphics Pipeline

FIG. 23 is a block diagram of another embodiment of a graphics processor2300. Elements of FIG. 23 having the same reference numbers (or names)as the elements of any other figure herein can operate or function inany manner similar to that described elsewhere herein, but are notlimited to such.

In some embodiments, graphics processor 2300 includes a geometrypipeline 2320, a media pipeline 2330, a display engine 2340, threadexecution logic 2350, and a render output pipeline 2370. In someembodiments, graphics processor 2300 is a graphics processor within amulti-core processing system that includes one or more general-purposeprocessing cores. The graphics processor is controlled by registerwrites to one or more control registers (not shown) or via commandsissued to graphics processor 2300 via a ring interconnect 2302. In someembodiments, ring interconnect 2302 couples graphics processor 2300 toother processing components, such as other graphics processors orgeneral-purpose processors. Commands from ring interconnect 2302 areinterpreted by a command streamer 2303, which supplies instructions toindividual components of the geometry pipeline 2320 or the mediapipeline 2330.

In some embodiments, command streamer 2303 directs the operation of avertex fetcher 2305 that reads vertex data from memory and executesvertex-processing commands provided by command streamer 2303. In someembodiments, vertex fetcher 2305 provides vertex data to a vertex shader2307, which performs coordinate space transformation and lightingoperations to each vertex. In some embodiments, vertex fetcher 2305 andvertex shader 2307 execute vertex-processing instructions by dispatchingexecution threads to execution units 2352A-2352B via a thread dispatcher2331.

In some embodiments, execution units 2352A-2352B are an array of vectorprocessors having an instruction set for performing graphics and mediaoperations. In some embodiments, execution units 2352A-2352B have anattached L1 cache 2351 that is specific for each array or shared betweenthe arrays. The cache can be configured as a data cache, an instructioncache, or a single cache that is partitioned to contain data andinstructions in different partitions.

In some embodiments, geometry pipeline 2320 includes tessellationcomponents to perform hardware-accelerated tessellation of 3D objects.In some embodiments, a programmable hull shader 2311 configures thetessellation operations. A programmable domain shader 2317 providesback-end evaluation of tessellation output. A tessellator 2313 operatesat the direction of hull shader 2311 and contains special purpose logicto generate a set of detailed geometric objects based on a coarsegeometric model that is provided as input to geometry pipeline 2320. Insome embodiments, if tessellation is not used, tessellation components(e.g., hull shader 2311, tessellator 2313, and domain shader 2317) canbe bypassed.

In some embodiments, complete geometric objects can be processed by ageometry shader 2319 via one or more threads dispatched to executionunits 2352A-2352B, or can proceed directly to the clipper 2329. In someembodiments, the geometry shader operates on entire geometric objects,rather than vertices or patches of vertices as in previous stages of thegraphics pipeline. If the tessellation is disabled the geometry shader2319 receives input from the vertex shader 2307. In some embodiments,geometry shader 2319 is programmable by a geometry shader program toperform geometry tessellation if the tessellation units are disabled.

Before rasterization, a clipper 2329 processes vertex data. The clipper2329 may be a fixed function clipper or a programmable clipper havingclipping and geometry shader functions. In some embodiments, arasterizer and depth test component 2373 in the render output pipeline2370 dispatches pixel shaders to convert the geometric objects into perpixel representations. In some embodiments, pixel shader logic isincluded in thread execution logic 2350. In some embodiments, anapplication can bypass the rasterizer and depth test component 2373 andaccess un-rasterized vertex data via a stream out unit 2323.

The graphics processor 2300 has an interconnect bus, interconnectfabric, or some other interconnect mechanism that allows data andmessage passing amongst the major components of the processor. In someembodiments, execution units 2352A-2352B and associated logic units(e.g., L1 cache 2351, sampler 2354, texture cache 2358, etc.)interconnect via a data port 2356 to perform memory access andcommunicate with render output pipeline components of the processor. Insome embodiments, sampler 2354, caches 2351, 2358 and execution units2352A-2352B each have separate memory access paths. In one embodimentthe texture cache 2358 can also be configured as a sampler cache.

In some embodiments, render output pipeline 2370 contains a rasterizerand depth test component 2373 that converts vertex-based objects into anassociated pixel-based representation. In some embodiments, therasterizer logic includes a windower/masker unit to perform fixedfunction triangle and line rasterization. An associated render cache2378 and depth cache 2379 are also available in some embodiments. Apixel operations component 2377 performs pixel-based operations on thedata, though in some instances, pixel operations associated with 2Doperations (e.g. bit block image transfers with blending) are performedby the 2D engine 2341, or substituted at display time by the displaycontroller 2343 using overlay display planes. In some embodiments, ashared L3 cache 2375 is available to all graphics components, allowingthe sharing of data without the use of main system memory.

In some embodiments, graphics processor media pipeline 2330 includes amedia engine 2337 and a video front-end 2334. In some embodiments, videofront-end 2334 receives pipeline commands from the command streamer2303. In some embodiments, media pipeline 2330 includes a separatecommand streamer. In some embodiments, video front-end 2334 processesmedia commands before sending the command to the media engine 2337. Insome embodiments, media engine 2337 includes thread spawningfunctionality to spawn threads for dispatch to thread execution logic2350 via thread dispatcher 2331.

In some embodiments, graphics processor 2300 includes a display engine2340. In some embodiments, display engine 2340 is external to processor2300 and couples with the graphics processor via the ring interconnect2302, or some other interconnect bus or fabric. In some embodiments,display engine 2340 includes a 2D engine 2341 and a display controller2343. In some embodiments, display engine 2340 contains special purposelogic capable of operating independently of the 3D pipeline. In someembodiments, display controller 2343 couples with a display device (notshown), which may be a system integrated display device, as in a laptopcomputer, or an external display device attached via a display deviceconnector.

In some embodiments, the geometry pipeline 2320 and media pipeline 2330are configurable to perform operations based on multiple graphics andmedia programming interfaces and are not specific to any one applicationprogramming interface (API). In some embodiments, driver software forthe graphics processor translates API calls that are specific to aparticular graphics or media library into commands that can be processedby the graphics processor. In some embodiments, support is provided forthe Open Graphics Library (OpenGL), Open Computing Language (OpenCL),and/or Vulkan graphics and compute API, all from the Khronos Group. Insome embodiments, support may also be provided for the Direct3D libraryfrom the Microsoft Corporation. In some embodiments, a combination ofthese libraries may be supported. Support may also be provided for theOpen Source Computer Vision Library (OpenCV). A future API with acompatible 3D pipeline would also be supported if a mapping can be madefrom the pipeline of the future API to the pipeline of the graphicsprocessor.

Graphics Pipeline Programming

FIG. 24A is a block diagram illustrating a graphics processor commandformat 2400 according to some embodiments. FIG. 24B is a block diagramillustrating a graphics processor command sequence 2410 according to anembodiment. The solid lined boxes in FIG. 24A illustrate the componentsthat are generally included in a graphics command while the dashed linesinclude components that are optional or that are only included in asub-set of the graphics commands. The exemplary graphics processorcommand format 2400 of FIG. 24A includes data fields to identify aclient 2402, a command operation code (opcode) 2404, and data 2406 forthe command. A sub-opcode 2405 and a command size 2408 are also includedin some commands.

In some embodiments, client 2402 specifies the client unit of thegraphics device that processes the command data. In some embodiments, agraphics processor command parser examines the client field of eachcommand to condition the further processing of the command and route thecommand data to the appropriate client unit. In some embodiments, thegraphics processor client units include a memory interface unit, arender unit, a 2D unit, a 3D unit, and a media unit. Each client unithas a corresponding processing pipeline that processes the commands.Once the command is received by the client unit, the client unit readsthe opcode 2404 and, if present, sub-opcode 2405 to determine theoperation to perform. The client unit performs the command usinginformation in data field 2406. For some commands an explicit commandsize 2408 is expected to specify the size of the command. In someembodiments, the command parser automatically determines the size of atleast some of the commands based on the command opcode. In someembodiments commands are aligned via multiples of a double word.

The flow diagram in FIG. 24B illustrates an exemplary graphics processorcommand sequence 2410. In some embodiments, software or firmware of adata processing system that features an embodiment of a graphicsprocessor uses a version of the command sequence shown to set up,execute, and terminate a set of graphics operations. A sample commandsequence is shown and described for purposes of example only asembodiments are not limited to these specific commands or to thiscommand sequence. Moreover, the commands may be issued as batch ofcommands in a command sequence, such that the graphics processor willprocess the sequence of commands in at least partially concurrence.

In some embodiments, the graphics processor command sequence 2410 maybegin with a pipeline flush command 2412 to cause any active graphicspipeline to complete the currently pending commands for the pipeline. Insome embodiments, the 3D pipeline 2422 and the media pipeline 2424 donot operate concurrently. The pipeline flush is performed to cause theactive graphics pipeline to complete any pending commands. In responseto a pipeline flush, the command parser for the graphics processor willpause command processing until the active drawing engines completepending operations and the relevant read caches are invalidated.Optionally, any data in the render cache that is marked ‘dirty’ can beflushed to memory. In some embodiments, pipeline flush command 2412 canbe used for pipeline synchronization or before placing the graphicsprocessor into a low power state.

In some embodiments, a pipeline select command 2413 is used when acommand sequence requires the graphics processor to explicitly switchbetween pipelines. In some embodiments, a pipeline select command 2413is required only once within an execution context before issuingpipeline commands unless the context is to issue commands for bothpipelines. In some embodiments, a pipeline flush command 2412 isrequired immediately before a pipeline switch via the pipeline selectcommand 2413.

In some embodiments, a pipeline control command 2414 configures agraphics pipeline for operation and is used to program the 3D pipeline2422 and the media pipeline 2424. In some embodiments, pipeline controlcommand 2414 configures the pipeline state for the active pipeline. Inone embodiment, the pipeline control command 2414 is used for pipelinesynchronization and to clear data from one or more cache memories withinthe active pipeline before processing a batch of commands.

In some embodiments, return buffer state commands 2416 are used toconfigure a set of return buffers for the respective pipelines to writedata. Some pipeline operations require the allocation, selection, orconfiguration of one or more return buffers into which the operationswrite intermediate data during processing. In some embodiments, thegraphics processor also uses one or more return buffers to store outputdata and to perform cross thread communication. In some embodiments, thereturn buffer state 2416 includes selecting the size and number ofreturn buffers to use for a set of pipeline operations.

The remaining commands in the command sequence differ based on theactive pipeline for operations. Based on a pipeline determination 2420,the command sequence is tailored to the 3D pipeline 2422 beginning withthe 3D pipeline state 2430 or the media pipeline 2424 beginning at themedia pipeline state 2440.

The commands to configure the 3D pipeline state 2430 include 3D statesetting commands for vertex buffer state, vertex element state, constantcolor state, depth buffer state, and other state variables that are tobe configured before 3D primitive commands are processed. The values ofthese commands are determined at least in part based on the particular3D API in use. In some embodiments, 3D pipeline state 2430 commands arealso able to selectively disable or bypass certain pipeline elements ifthose elements will not be used.

In some embodiments, 3D primitive 2432 command is used to submit 3Dprimitives to be processed by the 3D pipeline. Commands and associatedparameters that are passed to the graphics processor via the 3Dprimitive 2432 command are forwarded to the vertex fetch function in thegraphics pipeline. The vertex fetch function uses the 3D primitive 2432command data to generate vertex data structures. The vertex datastructures are stored in one or more return buffers. In someembodiments, 3D primitive 2432 command is used to perform vertexoperations on 3D primitives via vertex shaders. To process vertexshaders, 3D pipeline 2422 dispatches shader execution threads tographics processor execution units.

In some embodiments, 3D pipeline 2422 is triggered via an execute 2434command or event. In some embodiments, a register write triggers commandexecution. In some embodiments execution is triggered via a ‘go’ or‘kick’ command in the command sequence. In one embodiment, commandexecution is triggered using a pipeline synchronization command to flushthe command sequence through the graphics pipeline. The 3D pipeline willperform geometry processing for the 3D primitives. Once operations arecomplete, the resulting geometric objects are rasterized and the pixelengine colors the resulting pixels. Additional commands to control pixelshading and pixel back end operations may also be included for thoseoperations.

In some embodiments, the graphics processor command sequence 2410follows the media pipeline 2424 path when performing media operations.In general, the specific use and manner of programming for the mediapipeline 2424 depends on the media or compute operations to beperformed. Specific media decode operations may be offloaded to themedia pipeline during media decode. In some embodiments, the mediapipeline can also be bypassed and media decode can be performed in wholeor in part using resources provided by one or more general-purposeprocessing cores. In one embodiment, the media pipeline also includeselements for general-purpose graphics processor unit (GPGPU) operations,where the graphics processor is used to perform SIMD vector operationsusing computational shader programs that are not explicitly related tothe rendering of graphics primitives.

In some embodiments, media pipeline 2424 is configured in a similarmanner as the 3D pipeline 2422. A set of commands to configure the mediapipeline state 2440 are dispatched or placed into a command queue beforethe media object commands 2442. In some embodiments, commands for themedia pipeline state 2440 include data to configure the media pipelineelements that will be used to process the media objects. This includesdata to configure the video decode and video encode logic within themedia pipeline, such as encode or decode format. In some embodiments,commands for the media pipeline state 2440 also support the use of oneor more pointers to “indirect” state elements that contain a batch ofstate settings.

In some embodiments, media object commands 2442 supply pointers to mediaobjects for processing by the media pipeline. The media objects includememory buffers containing video data to be processed. In someembodiments, all media pipeline states must be valid before issuing amedia object command 2442. Once the pipeline state is configured andmedia object commands 2442 are queued, the media pipeline 2424 istriggered via an execute command 2444 or an equivalent execute event(e.g., register write). Output from media pipeline 2424 may then be postprocessed by operations provided by the 3D pipeline 2422 or the mediapipeline 2424. In some embodiments, GPGPU operations are configured andexecuted in a similar manner as media operations.

Graphics Software Architecture

FIG. 25 illustrates exemplary graphics software architecture for a dataprocessing system 2500 according to some embodiments. In someembodiments, software architecture includes a 3D graphics application2510, an operating system 2520, and at least one processor 2530. In someembodiments, processor 2530 includes a graphics processor 2532 and oneor more general-purpose processor core(s) 2534. The graphics application2510 and operating system 2520 each execute in the system memory 2550 ofthe data processing system.

In some embodiments, 3D graphics application 2510 contains one or moreshader programs including shader instructions 2512. The shader languageinstructions may be in a high-level shader language, such as the HighLevel Shader Language (HLSL) or the OpenGL Shader Language (GLSL). Theapplication also includes executable instructions 2514 in a machinelanguage suitable for execution by the general-purpose processor core2534. The application also includes graphics objects 2516 defined byvertex data.

In some embodiments, operating system 2520 is a Microsoft® Windows®operating system from the Microsoft Corporation, a proprietary UNIX-likeoperating system, or an open source UNIX-like operating system using avariant of the Linux kernel. The operating system 2520 can support agraphics API 2522 such as the Direct3D API, the OpenGL API, or theVulkan API. When the Direct3D API is in use, the operating system 2520uses a front-end shader compiler 2524 to compile any shader instructions2512 in HLSL into a lower-level shader language. The compilation may bea just-in-time (JIT) compilation or the application can perform shaderpre-compilation. In some embodiments, high-level shaders are compiledinto low-level shaders during the compilation of the 3D graphicsapplication 2510. In some embodiments, the shader instructions 2512 areprovided in an intermediate form, such as a version of the StandardPortable Intermediate Representation (SPIR) used by the Vulkan API.

In some embodiments, user mode graphics driver 2526 contains a back-endshader compiler 2527 to convert the shader instructions 2512 into ahardware specific representation. When the OpenGL API is in use, shaderinstructions 2512 in the GLSL high-level language are passed to a usermode graphics driver 2526 for compilation. In some embodiments, usermode graphics driver 2526 uses operating system kernel mode functions2528 to communicate with a kernel mode graphics driver 2529. In someembodiments, kernel mode graphics driver 2529 communicates with graphicsprocessor 2532 to dispatch commands and instructions.

IP Core Implementations

One or more aspects of at least one embodiment may be implemented byrepresentative code stored on a machine-readable medium which representsand/or defines logic within an integrated circuit such as a processor.For example, the machine-readable medium may include instructions whichrepresent various logic within the processor. When read by a machine,the instructions may cause the machine to fabricate the logic to performthe techniques described herein. Such representations, known as “IPcores,” are reusable units of logic for an integrated circuit that maybe stored on a tangible, machine-readable medium as a hardware modelthat describes the structure of the integrated circuit. The hardwaremodel may be supplied to various customers or manufacturing facilities,which load the hardware model on fabrication machines that manufacturethe integrated circuit. The integrated circuit may be fabricated suchthat the circuit performs operations described in association with anyof the embodiments described herein.

FIG. 26A is a block diagram illustrating an IP core development system2600 that may be used to manufacture an integrated circuit to performoperations according to an embodiment. The IP core development system2600 may be used to generate modular, re-usable designs that can beincorporated into a larger design or used to construct an entireintegrated circuit (e.g., an SOC integrated circuit). A design facility2630 can generate a software simulation 2610 of an IP core design in ahigh-level programming language (e.g., C/C++). The software simulation2610 can be used to design, test, and verify the behavior of the IP coreusing a simulation model 2612. The simulation model 2612 may includefunctional, behavioral, and/or timing simulations. A register transferlevel (RTL) design 2615 can then be created or synthesized from thesimulation model 2612. The RTL design 2615 is an abstraction of thebehavior of the integrated circuit that models the flow of digitalsignals between hardware registers, including the associated logicperformed using the modeled digital signals. In addition to an RTLdesign 2615, lower-level designs at the logic level or transistor levelmay also be created, designed, or synthesized. Thus, the particulardetails of the initial design and simulation may vary.

The RTL design 2615 or equivalent may be further synthesized by thedesign facility into a hardware model 2620, which may be in a hardwaredescription language (HDL), or some other representation of physicaldesign data. The HDL may be further simulated or tested to verify the IPcore design. The IP core design can be stored for delivery to a 3rdparty fabrication facility 2665 using non-volatile memory 2640 (e.g.,hard disk, flash memory, or any non-volatile storage medium).Alternatively, the IP core design may be transmitted (e.g., via theInternet) over a wired connection 2650 or wireless connection 2660. Thefabrication facility 2665 may then fabricate an integrated circuit thatis based at least in part on the IP core design. The fabricatedintegrated circuit can be configured to perform operations in accordancewith at least one embodiment described herein.

FIG. 26B illustrates a cross-section side view of an integrated circuitpackage assembly 2670, according to some embodiments described herein.The integrated circuit package assembly 2670 illustrates animplementation of one or more processor or accelerator devices asdescribed herein. The package assembly 2670 includes multiple units ofhardware logic 2672, 2674 connected to a substrate 2680. The logic 2672,2674 may be implemented at least partly in configurable logic orfixed-functionality logic hardware, and can include one or more portionsof any of the processor core(s), graphics processor(s), or otheraccelerator devices described herein. Each unit of logic 2672, 2674 canbe implemented within a semiconductor die and coupled with the substrate2680 via an interconnect structure 2673. The interconnect structure 2673may be configured to route electrical signals between the logic 2672,2674 and the substrate 2680, and can include interconnects such as, butnot limited to bumps or pillars. In some embodiments, the interconnectstructure 2673 may be configured to route electrical signals such as,for example, input/output (I/O) signals and/or power or ground signalsassociated with the operation of the logic 2672, 2674. In someembodiments, the substrate 2680 is an epoxy-based laminate substrate.The package substrate 2680 may include other suitable types ofsubstrates in other embodiments. The package assembly 2670 can beconnected to other electrical devices via a package interconnect 2683.The package interconnect 2683 may be coupled to a surface of thesubstrate 2680 to route electrical signals to other electrical devices,such as a motherboard, other chipset, or multi-chip module.

In some embodiments, the units of logic 2672, 2674 are electricallycoupled with a bridge 2682 that is configured to route electricalsignals between the logic 2672, 2674. The bridge 2682 may be a denseinterconnect structure that provides a route for electrical signals. Thebridge 2682 may include a bridge substrate composed of glass or asuitable semiconductor material. Electrical routing features can beformed on the bridge substrate to provide a chip-to-chip connectionbetween the logic 2672, 2674.

Although two units of logic 2672, 2674 and a bridge 2682 areillustrated, embodiments described herein may include more or fewerlogic units on one or more dies. The one or more dies may be connectedby zero or more bridges, as the bridge 2682 may be excluded when thelogic is included on a single die. Alternatively, multiple dies or unitsof logic can be connected by one or more bridges. Additionally, multiplelogic units, dies, and bridges can be connected together in otherpossible configurations, including three-dimensional configurations.

Exemplary System on a Chip Integrated Circuit

FIGS. 27-29B illustrate exemplary integrated circuits and associatedgraphics processors that may be fabricated using one or more IP cores,according to various embodiments described herein. In addition to whatis illustrated, other logic and circuits may be included, includingadditional graphics processors/cores, peripheral interface controllers,or general-purpose processor cores.

FIG. 27 is a block diagram illustrating an exemplary system on a chipintegrated circuit 2700 that may be fabricated using one or more IPcores, according to an embodiment. Exemplary integrated circuit 2700includes one or more application processor(s) 2705 (e.g., CPUs), atleast one graphics processor 2710, and may additionally include an imageprocessor 2715 and/or a video processor 2720, any of which may be amodular IP core from the same or multiple different design facilities.Integrated circuit 2700 includes peripheral or bus logic including a USBcontroller 2725, UART controller 2730, an SPI/SDIO controller 2735, andan I2S/I2C controller 2740. Additionally, the integrated circuit caninclude a display device 2745 coupled to one or more of ahigh-definition multimedia interface (HDMI) controller 2750 and a mobileindustry processor interface (MIPI) display interface 2755. Storage maybe provided by a flash memory subsystem 2760 including flash memory anda flash memory controller. Memory interface may be provided via a memorycontroller 2765 for access to SDRAM or SRAM memory devices. Someintegrated circuits additionally include an embedded security engine2770.

FIGS. 28A-28B are block diagrams illustrating exemplary graphicsprocessors for use within an SoC, according to embodiments describedherein. FIG. 28A illustrates an exemplary graphics processor 2810 of asystem on a chip integrated circuit that may be fabricated using one ormore IP cores, according to an embodiment. FIG. 28B illustrates anadditional exemplary graphics processor 2840 of a system on a chipintegrated circuit that may be fabricated using one or more IP cores,according to an embodiment. Graphics processor 2810 of FIG. 28A is anexample of a low power graphics processor core. Graphics processor 2840of FIG. 28B is an example of a higher performance graphics processorcore. Each of the graphics processors 2810, 2840 can be variants of thegraphics processor 2710 of FIG. 27.

As shown in FIG. 28A, graphics processor 2810 includes a vertexprocessor 2805 and one or more fragment processor(s) 2815A-2815N (e.g.,2815A, 2815B, 2815C, 2815D, through 2815N-1, and 2815N). Graphicsprocessor 2810 can execute different shader programs via separate logic,such that the vertex processor 2805 is optimized to execute operationsfor vertex shader programs, while the one or more fragment processor(s)2815A-2815N execute fragment (e.g., pixel) shading operations forfragment or pixel shader programs. The vertex processor 2805 performsthe vertex processing stage of the 3D graphics pipeline and generatesprimitives and vertex data. The fragment processor(s) 2815A-2815N usethe primitive and vertex data generated by the vertex processor 2805 toproduce a framebuffer that is displayed on a display device. In oneembodiment, the fragment processor(s) 2815A-2815N are optimized toexecute fragment shader programs as provided for in the OpenGL API,which may be used to perform similar operations as a pixel shaderprogram as provided for in the Direct 3D API.

Graphics processor 2810 additionally includes one or more memorymanagement units (MMUs) 2820A-2820B, cache(s) 2825A-2825B, and circuitinterconnect(s) 2830A-2830B. The one or more MMU(s) 2820A-2820B providefor virtual to physical address mapping for the graphics processor 2810,including for the vertex processor 2805 and/or fragment processor(s)2815A-2815N, which may reference vertex or image/texture data stored inmemory, in addition to vertex or image/texture data stored in the one ormore cache(s) 2825A-2825B. In one embodiment the one or more MMU(s)2820A-2820B may be synchronized with other MMUs within the system,including one or more MMUs associated with the one or more applicationprocessor(s) 2705, image processor 2715, and/or video processor 2720 ofFIG. 27, such that each processor 2705-2720 can participate in a sharedor unified virtual memory system. The one or more circuitinterconnect(s) 2830A-2830B enable graphics processor 2810 to interfacewith other IP cores within the SoC, either via an internal bus of theSoC or via a direct connection, according to embodiments.

As shown FIG. 28B, graphics processor 2840 includes the one or moreMMU(s) 2820A-2820B, caches 2825A-2825B, and circuit interconnects2830A-2830B of the graphics processor 2810 of FIG. 28A. Graphicsprocessor 2840 includes one or more shader core(s) 2855A-2855N (e.g.,2855A, 2855B, 2855C, 2855D, 2855E, 2855F, through 2855N-1, and 2855N),which provides for a unified shader core architecture in which a singlecore or type or core can execute all types of programmable shader code,including shader program code to implement vertex shaders, fragmentshaders, and/or compute shaders. The exact number of shader corespresent can vary among embodiments and implementations. Additionally,graphics processor 2840 includes an inter-core task manager 2845, whichacts as a thread dispatcher to dispatch execution threads to one or moreshader cores 2855A-2855N and a tiling unit 2858 to accelerate tilingoperations for tile-based rendering, in which rendering operations for ascene are subdivided in image space, for example to exploit localspatial coherence within a scene or to optimize use of internal caches.

FIGS. 29A-29B illustrate additional exemplary graphics processor logicaccording to embodiments described herein. FIG. 29A illustrates agraphics core 2900 that may be included within the graphics processor2710 of FIG. 27, and may be a unified shader core 2855A-2855N as in FIG.28B. FIG. 29B illustrates a highly-parallel general-purpose graphicsprocessing unit 2930 suitable for deployment on a multi-chip module.

As shown in FIG. 29A, the graphics core 2900 includes a sharedinstruction cache 2902, a texture unit 2918, and a cache/shared memory2920 that are common to the execution resources within the graphics core2900. The graphics core 2900 can include multiple slices 2901A-2901N orpartition for each core, and a graphics processor can include multipleinstances of the graphics core 2900. The slices 2901A-2901N can includesupport logic including a local instruction cache 2904A-2904N, a threadscheduler 2906A-2906N, a thread dispatcher 2908A-2908N, and a set ofregisters 2910A. To perform logic operations, the slices 2901A-2901N caninclude a set of additional function units (AFUs 2912A-2912N),floating-point units (FPU 2914A-2914N), integer arithmetic logic units(ALUs 2916-2916N), address computational units (ACU 2913A-2913N),double-precision floating-point units (DPFPU 2915A-2915N), and matrixprocessing units (MPU 2917A-2917N).

Some of the computational units operate at a specific precision. Forexample, the FPUs 2914A-2914N can perform single-precision (32-bit) andhalf-precision (16-bit) floating point operations, while the DPFPUs2915A-2915N perform double precision (64-bit) floating point operations.The ALUs 2916A-2916N can perform variable precision integer operationsat 8-bit, 16-bit, and 32-bit precision, and can be configured for mixedprecision operations. The MPUs 2917A-2917N can also be configured formixed precision matrix operations, including half-precision floatingpoint and 8-bit integer operations. The MPUs 2917-2917N can perform avariety of matrix operations to accelerate machine learning applicationframeworks, including enabling support for accelerated general matrix tomatrix multiplication (GEMM). The AFUs 2912A-2912N can performadditional logic operations not supported by the floating-point orinteger units, including trigonometric operations (e.g., Sine, Cosine,etc.).

As shown in FIG. 29B, a general-purpose processing unit (GPGPU) 2930 canbe configured to enable highly-parallel compute operations to beperformed by an array of graphics processing units. Additionally, theGPGPU 2930 can be linked directly to other instances of the GPGPU tocreate a multi-GPU cluster to improve training speed for particularlydeep neural networks. The GPGPU 2930 includes a host interface 2932 toenable a connection with a host processor. In one embodiment the hostinterface 2932 is a PCI Express interface. However, the host interfacecan also be a vendor specific communications interface or communicationsfabric. The GPGPU 2930 receives commands from the host processor anduses a global scheduler 2934 to distribute execution threads associatedwith those commands to a set of compute clusters 2936A-2936H. Thecompute clusters 2936A-2936H share a cache memory 2938. The cache memory2938 can serve as a higher-level cache for cache memories within thecompute clusters 2936A-2936H.

The GPGPU 2930 includes memory 2944A-2934B coupled with the computeclusters 2936A-2936H via a set of memory controllers 2942A-2942B. Invarious embodiments, the memory 2944A-2934B can include various types ofmemory devices including dynamic random access memory (DRAM) or graphicsrandom access memory, such as synchronous graphics random access memory(SGRAM), including graphics double data rate (GDDR) memory.

In one embodiment the compute clusters 2936A-2936H each include a set ofgraphics cores, such as the graphics core 2900 of FIG. 29A, which caninclude multiple types of integer and floating point logic units thatcan perform computational operations at a range of precisions includingsuited for machine learning computations. For example and in oneembodiment at least a subset of the floating point units in each of thecompute clusters 2936A-2936H can be configured to perform 16-bit or32-bit floating point operations, while a different subset of thefloating point units can be configured to perform 64-bit floating pointoperations.

Multiple instances of the GPGPU 2930 can be configured to operate as acompute cluster. The communication mechanism used by the compute clusterfor synchronization and data exchange varies across embodiments. In oneembodiment the multiple instances of the GPGPU 2930 communicate over thehost interface 2932. In one embodiment the GPGPU 2930 includes an I/Ohub 2939 that couples the GPGPU 2930 with a GPU link 2940 that enables adirect connection to other instances of the GPGPU. In one embodiment theGPU link 2940 is coupled to a dedicated GPU-to-GPU bridge that enablescommunication and synchronization between multiple instances of theGPGPU 2930. In one embodiment the GPU link 2940 couples with a highspeed interconnect to transmit and receive data to other GPGPUs orparallel processors. In one embodiment the multiple instances of theGPGPU 2930 are located in separate data processing systems andcommunicate via a network device that is accessible via the hostinterface 2932. In one embodiment the GPU link 2940 can be configured toenable a connection to a host processor in addition to or as analternative to the host interface 2932.

While the illustrated configuration of the GPGPU 2930 can be configuredto train neural networks, one embodiment provides alternateconfiguration of the GPGPU 2930 that can be configured for deploymentwithin a high performance or low power inferencing platform. In aninferencing configuration the GPGPU 2930 includes fewer of the computeclusters 2936A-2936H relative to the training configuration.Additionally, the memory technology associated with the memory2944A-2934B may differ between inferencing and training configurations,with higher bandwidth memory technologies devoted to trainingconfigurations. In one embodiment the inferencing configuration of theGPGPU 2930 can support inferencing specific instructions. For example,an inferencing configuration can provide support for one or more 8-bitinteger dot product instructions, which are commonly used duringinferencing operations for deployed neural networks.

Head-Mounted Display System Overview

FIG. 30 shows a head mounted display (HMD) system 3000 that is beingworn by a user while experiencing an immersive environment such as, forexample, a virtual reality (VR) environment, an augmented reality (AR)environment, a multi-player three-dimensional (3D) game, and so forth.In the illustrated example, one or more straps 3020 hold a frame 3002 ofthe HMD system 3000 in front of the eyes of the user. Accordingly, aleft-eye display 3004 may be positioned to be viewed by the left eye ofthe user and a right-eye display 3006 may be positioned to be viewed bythe right eye of the user. The left-eye display 3004 and the right-eyedisplay 3006 may alternatively be integrated into a single display incertain examples such as, for example, a smart phone being worn by theuser. In the case of AR, the displays 3004, 3006 may be view-throughdisplays that permit the user to view the physical surroundings, withother rendered content (e.g., virtual characters, informationalannotations, heads up display/HUD) being presented on top a live feed ofthe physical surroundings.

In one example, the frame 3002 includes a left look-down camera 3008 tocapture images from an area generally in front of the user and beneaththe left eye (e.g., left hand gestures). Additionally, a right look-downcamera 3010 may capture images from an area generally in front of theuser and beneath the right eye (e.g., right hand gestures). Theillustrated frame 3002 also includes a left look-front camera 3012 and aright look-front camera 3014 to capture images in front of the left andright eyes, respectively, of the user. The frame 3002 may also include aleft look-side camera 3016 to capture images from an area to the left ofthe user and a right look-side camera 3018 to capture images from anarea to the right of the user.

The images captured by the cameras 3008, 3010, 3012, 3014, 3016, 3018,which may have overlapping fields of view, may be used to detectgestures made by the user as well as to analyze and/or reproduce theexternal environment on the displays 3004, 3006. In one example, thedetected gestures are used by a graphics processing architecture (e.g.,internal and/or external) to render and/or control a virtualrepresentation of the user in a 3D game. Indeed, the overlapping fieldsof view may enable the capture of gestures made by other individuals(e.g., in a multi-player game), where the gestures of other individualsmay be further used to render/control the immersive experience. Theoverlapping fields of view may also enable the HMD system 3000 toautomatically detect obstructions or other hazards near the user. Suchan approach may be particularly advantageous in advanced driverassistance system (ADAS) applications.

In one example, providing the left look-down camera 3008 and the rightlook-down camera 3010 with overlapping fields of view provides astereoscopic view having an increased resolution. The increasedresolution may in turn enable very similar user movements to bedistinguished from one another (e.g., at sub-millimeter accuracy). Theresult may be an enhanced performance of the HMD system 3000 withrespect to reliability. Indeed, the illustrated solution may be usefulin a wide variety of applications such as, for example, coloringinformation in AR settings, exchanging virtual tools/devices betweenusers in a multi-user environment, rendering virtual items (e.g.,weapons, swords, staffs), and so forth. Gestures of other objects, limbsand/or body parts may also be detected and used to render/control thevirtual environment. For example, myelographic signals,electroencephalographic signals, eye tracking, breathing or puffing,hand motions, etc., may be tracked in real-time, whether from the weareror another individual in a shared environment. The images captured bythe cameras 3008, 3010, 3012, 3014, 3016, 3018, may also serve ascontextual input. For example, it might be determined that the user isindicating a particular word to edit or key to press in a wordprocessing application, a particular weapon to deployed or a traveldirection in a game, and so forth.

Additionally, the images captured by the cameras 3008, 3010, 3012, 3014,3016, 3018, may be used to conduct shared communication or networkedinteractivity in equipment operation, medical training, and/orremote/tele-operation guidance applications. Task specific gesturelibraries or neural network machine learning could enable toolidentification and feedback for a task. For example, a virtual tool thattranslates into remote, real actions may be enabled. In yet anotherexample, the HMD system 3000 translates the manipulation of a virtualdrill within a virtual scene to the remote operation of a drill on arobotic device deployed to search a collapsed building. Moreover, theHMD system 3000 may be programmable to the extent that it includes, forexample, a protocol that enables the user to add a new gesture to a listof identifiable gestures associated with user actions.

In addition, the various cameras in the HMD 3000 may be configurable todetect spectrum frequencies in addition to the visible wavelengths ofthe spectrum. Multi-spectral imaging capabilities in the input camerasallows position tracking of the user and/or objects by eliminatingnonessential image features (e.g., background noise). For example, inaugmented reality (AR) applications such as surgery, instruments andequipment may be tracked by their infrared reflectivity without the needfor additional tracking aids. Moreover, HMD 3000 could be employed insituations of low visibility where a “live feed” from the variouscameras could be enhanced or augmented through computer analysis anddisplayed to the user as visual or audio cues.

The HMD system 3000 may also forego performing any type of datacommunication with a remote computing system or need power cables (e.g.,independent mode of operation). In this regard, the HMD system 3000 maybe a “cordless” device having a power unit that enables the HMD system3000 to operate independently of external power systems. Accordingly,the user might play a full featured game without being tethered toanother device (e.g., game console) or power supply. In a wordprocessing example, the HMD system 3000 might present a virtual keyboardand/or virtual mouse on the displays 3004 and 3006 to provide a virtualdesktop or word processing scene. Thus, gesture recognition datacaptured by one or more of the cameras may represent user typingactivities on the virtual keyboard or movements of the virtual mouse.Advantages include, but are not limited to, ease of portability andprivacy of the virtual desktop from nearby individuals. The underlyinggraphics processing architecture may support compression and/ordecompression of video and audio signals. Moreover, providing separateimages to the left eye and right eye of the user may facilitate therendering, generation and/or perception of 3D scenes. The relativepositions of the left-eye display 3004 and the right-eye display 3006may also be adjustable to match variations in eye separation betweendifferent users.

The number of cameras illustrated in FIG. 30 is to facilitate discussiononly. Indeed, the HMD system 3000 may include less than six or more thansix cameras, depending on the circumstances.

The display 1120 (FIG. 11), the display assembly 1360 (FIG. 13) and/orthe HMD system 3000 may include a light field display. In one example,the 3D graphics application 2510 (FIG. 25) performs processing block 628(FIG. 6E) of the method 626 (FIG. 6E) and the user mode graphics driver2526 (FIG. 25) performs processing block 1530 of the method 626 (FIG.6E) to support the enhanced data formatting techniques described herein.Additionally, the graphics processing pipeline 500 (FIG. 5) may bemodified to support the re-projection, foveation, hierarchical cullingand image warping solutions described herein. Moreover, a tiling unitmay be modified to populate tile bins as described herein.

Additional Notes and Examples

Example 1 may include a performance-enhanced graphics apparatuscomprising one or more substrates and logic coupled to the one or moresubstrates, wherein the logic is implemented in one or more ofconfigurable logic or fixed-functionality hardware logic, the logiccoupled to the one or more substrates to identify a pixel location withrespect to a plurality of display planes, store image data associatedwith the pixel location and the plurality of display planes to adjacentmemory locations, and simultaneously render the image data from theadjacent memory locations across the plurality of display planes.

Example 2 may include the apparatus of Example 1, wherein the logiccoupled to the one or more substrates is to dispatch a singleinstruction multiple data (SIMD) instruction to a plurality of graphicsexecution units to simultaneously render the image data.

Example 3 may include the apparatus of Example 1, wherein the image datais to be further associated with a pixel subspan containing the pixellocation.

Example 4 may include the apparatus of Example 1, wherein the logiccoupled to the one or more substrates is to transpose the simultaneouslyrendered image data to a surface layout associated with the plurality ofdisplay planes.

Example 5 may include the apparatus of Example 1, wherein the adjacentmemory locations are to be within a single cache line.

Example 6 may include the apparatus of Example 1, wherein the logiccoupled to the one or more substrates is to render a source viewassociated with a first display plane in the plurality of displayplanes, re-project the rendered source view to a second display plane inthe plurality of display planes to obtain a re-projected view, and fillone or more holes in the re-projected view based on one or more ofextended field of view data corresponding to the source view,rasterization data corresponding to the source view or rasterizationdata corresponding to the re-projected view.

Example 7 may include the apparatus of Example 6, wherein when the oneor more holes are filled based on the extended field of view data, there-projected view has a non-extended field of view.

Example 8 may include the apparatus of Example 7, wherein when the oneor more holes are filled based on the rasterization data correspondingto the source view, the logic coupled to the one or more substrates isto disable a depth test during rendering of the source view, and conductthe depth test during filling of the one or more holes in there-projected view.

Example 9 may include the apparatus of Example 7, wherein when the oneor more holes are filled based on the rasterization data correspondingto the re-projected view, the logic coupled to the one or moresubstrates is to pre-populate a depth buffer during re-projection of therendered source view, and conduct a depth test during filling of the oneor more holes based on data in the depth buffer.

Example 10 may include the apparatus of Example 1, wherein the logiccoupled to the one or more substrates is to determine a focus pointrelative to the plurality of display planes, and vary, on a per displayplane basis, a resolution of scene content presented on the plurality ofdisplay planes based on the focus point.

Example 11 may include the apparatus of Example 10, wherein the logiccoupled to the one or more substrates is to vary, on the per displayplane basis, a view density of the scene content presented on theplurality of display planes based on the focus point.

Example 12 may include the apparatus of Example 10, wherein the logiccoupled to the one or more substrates is to vary, on the per displayplane basis, a view update frequency of the scene content presented onthe plurality of display planes based on the focus point.

Example 13 may include the apparatus of Example 10, wherein the logiccoupled to the one or more substrates is to separate peripheral viewsinto bins having one or more of different resolutions, different viewdensities or different update frequencies.

Example 14 may include the apparatus of Example 1, wherein the logiccoupled to the one or more substrates is to determine a set ofprimitives associated with the plurality of display planes, and conducta hierarchical sequence of culling operations on the set of primitives.

Example 15 may include the apparatus of Example 14, wherein thehierarchical sequence of culling operations is to include a nearplane-far plane culling operation that rejects primitives behind afarthest display plane in the plurality of display planes and rejectsprimitives in front of a nearest display plane in the plurality ofdisplay planes.

Example 16 may include the apparatus of Example 15, wherein thehierarchical sequence of culling operations is to include a coarsefrustum culling operation that is conducted on a per eye basis and afterthe near plane-far plane culling operation, and wherein the coarsefrustum culling operation is to reject primitives outside a top frustumplane of a topmost viewport, a bottom frustum plane of a bottommostviewport, a left frustum plane of a leftmost viewport and a rightfrustum plane of a rightmost viewport.

Example 17 may include the apparatus of Example 16, wherein thehierarchical sequence of culling operations is to include a fine frustumculling operation that is conducted after the coarse frustum cullingoperation, and wherein the logic coupled to the one or more substratesis to populate one or more tile bins with primitives that pass the finefrustum culling operation.

Example 18 may include the apparatus of Example 1, wherein the logiccoupled to the one or more substrates is to identify first image dataassociated with scene content on a first display plane in the pluralityof display planes, identify a first position change between the scenecontent on the first display plane and the scene content on a seconddisplay plane in the plurality of display planes, and approximate, basedon the first image data and the first position change, second image dataassociated with the scene content on the second display plane.

Example 19 may include the apparatus of Example 18, wherein the logiccoupled to the one or more substrates is to identify a second positionchange between the scene content on the first display plane and thescene content on a third display plane in the plurality of displayplanes, and approximate, based on the first image data and the secondposition change, third image data associated with the scene content onthe third display plane.

Example 20 may include an apparatus comprising one or more substrates,and logic coupled to the one or more substrates, wherein the logic isimplemented in one or more of configurable logic or fixed-functionalityhardware logic, the logic coupled to the one or more substrates torender a source view associated with a first display plane in aplurality of display planes, re-project the rendered source view to asecond display plane in the plurality of display planes to obtain are-projected view, and fill one or more holes in the re-projected viewbased on one or more of extended field of view data corresponding to thesource view, rasterization data corresponding to the source view orrasterization data corresponding to the re-projected view.

Example 21 may include the apparatus of Example 20, wherein when the oneor more holes are filled based on the extended field of view data, there-projected view has a non-extended field of view.

Example 22 may include the apparatus of Example 20, wherein when the oneor more holes are filled based on the rasterization data correspondingto the source view, the logic coupled to the one or more substrates isto disable a depth test during rendering of the source view, and conductthe depth test during filling of the one or more holes in there-projected view.

Example 23 may include the apparatus of Example 20, wherein when the oneor more holes are filled based on the rasterization data correspondingto the re-projected view, the logic coupled to the one or moresubstrates is to pre-populate a depth buffer during re-projection of therendered source view, and conduct a depth test during filling of the oneor more holes based on data in the depth buffer.

Example 24 may include the apparatus of Example 20, wherein the logiccoupled to the one or more substrates is to determine a focus pointrelative to the plurality of display planes, and vary, on a per displayplane basis, a resolution of scene content presented on the plurality ofdisplay planes based on the focus point.

Example 25 may include the apparatus of Example 24, wherein the logiccoupled to the one or more substrates is to vary, on the per displayplane basis, a view density of the scene content presented on theplurality of display planes based on the focus point.

Example 26 may include the apparatus of Example 24, wherein the logiccoupled to the one or more substrates is to vary, on the per displayplane basis, a view update frequency of the scene content presented onthe plurality of display planes based on the focus point.

Example 27 may include the apparatus of Example 24, wherein the logiccoupled to the one or more substrates is to separate peripheral viewsinto bins having one or more of different resolutions, different viewdensities or different update frequencies.

Example 28 may include the apparatus of Example 20, wherein the logiccoupled to the one or more substrates is to determine a set ofprimitives associated with the plurality of display planes, and conducta hierarchical sequence of culling operations on the set of primitives.

Example 29 may include the apparatus of Example 28, wherein thehierarchical sequence of culling operations is to include a nearplane-far plane culling operation that rejects primitives behind afarthest display plane in the plurality of display planes and rejectsprimitives in front of a nearest display plane in the plurality ofdisplay planes.

Example 30 may include the apparatus of Example 29, wherein thehierarchical sequence of culling operations is to include a coarsefrustum culling operation that is conducted on a per eye basis and afterthe near plane-far plane culling operation, and wherein the coarsefrustum culling operation is to reject primitives outside a top frustumplane of a topmost viewport, a bottom frustum plane of a bottommostviewport, a left frustum plane of a leftmost viewport and a rightfrustum plane of a rightmost viewport.

Example 31 may include the apparatus of Example 30, wherein thehierarchical sequence of culling operations is to include a fine frustumculling operation that is conducted after the coarse frustum cullingoperation, and wherein the logic coupled to the one or more substratesis to populate one or more tile bins with primitives that pass the finefrustum culling operation.

Example 32 may include the apparatus of Example 20, wherein the logiccoupled to the one or more substrates is to identify first image dataassociated with scene content on a first display plane in the pluralityof display planes, identify a first position change between the scenecontent on the first display plane and the scene content on a seconddisplay plane in the plurality of display planes, and approximate, basedon the first image data and the first position change, second image dataassociated with the scene content on the second display plane.

Example 33 may include the apparatus of Example 32, wherein the logiccoupled to the one or more substrates is to identify a second positionchange between the scene content on the first display plane and thescene content on a third display plane in the plurality of displayplanes, and approximate, based on the first image data and the secondposition change, third image data associated with the scene content onthe third display plane.

Example 34 may include an apparatus comprising one or more substrates,and logic coupled to the one or more substrates, wherein the logic isimplemented in one or more of configurable logic or fixed-functionalityhardware logic, the logic coupled to the one or more substrates todetermine a focus point relative to a plurality of display planes, andvary, on a per display plane basis, a resolution of scene contentpresented on the plurality of display planes based on the focus point.

Example 35 may include the apparatus of Example 34, wherein the logiccoupled to the one or more substrates is to vary, on the per displayplane basis, a view density of the scene content presented on theplurality of display planes based on the focus point.

Example 36 may include the apparatus of Example 34, wherein the logiccoupled to the one or more substrates is to vary, on the per displayplane basis, a view update frequency of the scene content presented onthe plurality of display planes based on the focus point.

Example 37 may include the apparatus of Example 34, wherein the logiccoupled to the one or more substrates is to separate peripheral viewsinto bins having one or more of different resolutions, different viewdensities or different update frequencies.

Example 38 may include the apparatus of Example 34, wherein the logiccoupled to the one or more substrates is to determine a set ofprimitives associated with the plurality of display planes, and conducta hierarchical sequence of culling operations on the set of primitives.

Example 39 may include the apparatus of Example 38, wherein thehierarchical sequence of culling operations is to include a nearplane-far plane culling operation that rejects primitives behind afarthest display plane in the plurality of display planes and rejectsprimitives in front of a nearest display plane in the plurality ofdisplay planes.

Example 40 may include the apparatus of Example 39, wherein thehierarchical sequence of culling operations is to include a coarsefrustum culling operation that is conducted on a per eye basis and afterthe near plane-far plane culling operation, and wherein the coarsefrustum culling operation is to reject primitives outside a top frustumplane of a topmost viewport, a bottom frustum plane of a bottommostviewport, a left frustum plane of a leftmost viewport and a rightfrustum plane of a rightmost viewport.

Example 41 may include the apparatus of Example 40, wherein thehierarchical sequence of culling operations is to include a fine frustumculling operation that is conducted after the coarse frustum cullingoperation, and wherein the logic coupled to the one or more substratesis to populate one or more tile bins with primitives that pass the finefrustum culling operation.

Example 42 may include the apparatus of Example 34, wherein the logiccoupled to the one or more substrates is to identify first image dataassociated with the scene content on a first display plane in theplurality of display planes, identify a first position change betweenthe scene content on the first display plane and the scene content on asecond display plane in the plurality of display planes, andapproximate, based on the first image data and the first positionchange, second image data associated with the scene content on thesecond display plane.

Example 43 may include the apparatus of Example 42, wherein the logiccoupled to the one or more substrates is to identify a second positionchange between the scene content on the first display plane and thescene content on a third display plane in the plurality of displayplanes, and approximate, based on the first image data and the secondposition change, third image data associated with the scene content onthe third display plane.

Example 44 may include an apparatus comprising one or more substrates,and logic coupled to the one or more substrates, wherein the logic isimplemented in one or more of configurable logic or fixed-functionalityhardware logic, the logic coupled to the one or more substrates todetermine a set of primitives associated with a plurality of displayplanes, and conduct a hierarchical sequence of culling operations on theset of primitives.

Example 45 may include the apparatus of Example 44, wherein thehierarchical sequence of culling operations is to include a nearplane-far plane culling operation that rejects primitives behind afarthest display plane in the plurality of display planes and rejectsprimitives in front of a nearest display plane in the plurality ofdisplay planes.

Example 46 may include the apparatus of Example 45, wherein thehierarchical sequence of culling operations is to include a coarsefrustum culling operation that is conducted on a per eye basis and afterthe near plane-far plane culling operation, and wherein the coarsefrustum culling operation is to reject primitives outside a top frustumplane of a topmost viewport, a bottom frustum plane of a bottommostviewport, a left frustum plane of a leftmost viewport and a rightfrustum plane of a rightmost viewport.

Example 47 may include the apparatus of Example 46, wherein thehierarchical sequence of culling operations is to include a fine frustumculling operation that is conducted after the coarse frustum cullingoperation, and wherein the logic coupled to the one or more substratesis to populate one or more tile bins with primitives that pass the finefrustum culling operation.

Example 48 may include the apparatus of Example 44, wherein the logiccoupled to the one or more substrates to identify first image dataassociated with scene content on a first display plane in the pluralityof display planes, identify a first position change between the scenecontent on the first display plane and the scene content on a seconddisplay plane in the plurality of display planes, and approximate, basedon the first image data and the first position change, second image dataassociated with the scene content on the second display plane.

Example 49 may include the apparatus of Example 48, wherein the logiccoupled to the one or more substrates is to identify a second positionchange between the scene content on the first display plane and thescene content on a third display plane in the plurality of displayplanes, and approximate, based on the first image data and the secondposition change, third image data associated with the scene content onthe third display plane.

Example 50 may include an apparatus comprising one or more substrates,and logic coupled to the one or more substrates, wherein the logic isimplemented in one or more of configurable logic or fixed-functionalityhardware logic, the logic coupled to the one or more substrates toidentify first image data associated with scene content on a firstdisplay plane in a plurality of display planes, identify a firstposition change between the scene content on the first display plane andthe scene content on a second display plane in the plurality of displayplanes, and approximate, based on the first image data and the firstposition change, second image data associated with the scene content onthe second display plane.

Example 51 may include the apparatus of Example 50, wherein the logiccoupled to the one or more substrates is to identify a second positionchange between the scene content on the first display plane and thescene content on a third display plane in the plurality of displayplanes, and approximate, based on the first image data and the secondposition change, third image data associated with the scene content onthe third display plane.

Example 52 may include a method of operating a performance-enhancedgraphics apparatus, comprising identifying a pixel location with respectto a plurality of display planes, storing image data associated with thepixel location and the plurality of display planes to adjacent memorylocations, and simultaneously rendering the image data from the adjacentmemory locations across the plurality of display planes.

Example 53 may include the method of Example 52, further includingdispatching a single instruction multiple data (SIMD) instruction to aplurality of graphics execution units to simultaneously rendering theimage data.

Example 54 may include the method of Example 52, wherein the image datais further associated with a pixel subspan containing the pixellocation.

Example 55 may include the method of Example 52, further includingtransposing the simultaneously rendered image data to a surface layoutassociated with the plurality of display planes.

Example 56 may include the method of Example 52, wherein the adjacentmemory locations are within a single cache line.

Example 57 may include the method of Example 52, further includingrendering a source view associated with a first display plane in theplurality of display planes, re-projecting the rendered source view to asecond display plane in the plurality of display planes to obtain are-projected view, and filling one or more holes in the re-projectedview based on one or more of extended field of view data correspondingto the source view, rasterization data corresponding to the source viewor rasterization data corresponding to the re-projected view.

Example 58 may include the method of Example 57, wherein when the one ormore holes are filled based on the extended field of view data, there-projected view has a non-extended field of view.

Example 59 may include the method of Example 58, wherein when the one ormore holes are filled based on the rasterization data corresponding tothe source view, the method further includes disabling a depth testduring rendering of the source view, and conducting the depth testduring filling of the one or more holes in the re-projected view.

Example 60 may include the method of Example 58, wherein when the one ormore holes are filled based on the rasterization data corresponding tothe re-projected view, the method further includes pre-populating adepth buffer during re-projection of the rendered source view, andconducting a depth test during filling of the one or more holes based ondata in the depth buffer.

Example 61 may include the method of Example 52, further includingdetermining a focus point relative to the plurality of display planes,and varying, on a per display plane basis, a resolution of scene contentpresented on the plurality of display planes based on the focus point.

Example 62 may include the method of Example 61, wherein the methodfurther includes varying, on the per display plane basis, a view densityof the scene content presented on the plurality of display planes basedon the focus point.

Example 63 may include the method of Example 61, wherein the methodfurther includes varying, on the per display plane basis, a view updatefrequency of the scene content presented on the plurality of displayplanes based on the focus point.

Example 64 may include the method of Example 61, wherein the methodfurther includes separating peripheral views into bins having one ormore of different resolutions, different view densities or differentupdate frequencies.

Example 65 may include the method of Example 52, further includingdetermining a set of primitives associated with the plurality of displayplanes, and conducting a hierarchical sequence of culling operations onthe set of primitives.

Example 66 may include the method of Example 65, wherein thehierarchical sequence of culling operations includes a near plane-farplane culling operation that rejects primitives behind a farthestdisplay plane in the plurality of display planes and rejects primitivesin front of a nearest display plane in the plurality of display planes.

Example 67 may include the method of Example 66, wherein thehierarchical sequence of culling operations includes a coarse frustumculling operation that is conducted on a per eye basis and after thenear plane-far plane culling operation, and wherein the coarse frustumculling operation is to reject primitives outside a top frustum plane ofa topmost viewport, a bottom frustum plane of a bottommost viewport, aleft frustum plane of a leftmost viewport and a right frustum plane of arightmost viewport.

Example 68 may include the method of Example 67, wherein thehierarchical sequence of culling operations includes a fine frustumculling operation that is conducted after the coarse frustum cullingoperation, and wherein the logic coupled to the one or more substratesis to populate one or more tile bins with primitives that pass the finefrustum culling operation.

Example 69 may include the method of Example 52, further includingidentifying first image data associated with scene content on a firstdisplay plane in the plurality of display planes, identifying a firstposition change between the scene content on the first display plane andthe scene content on a second display plane in the plurality of displayplanes, and approximating, based on the first image data and the firstposition change, second image data associated with the scene content onthe second display plane.

Example 70 may include the method of Example 69, further includingidentifying a second position change between the scene content on thefirst display plane and the scene content on a third display plane inthe plurality of display planes, and approximating, based on the firstimage data and the second position change, third image data associatedwith the scene content on the third display plane.

Example 71 may include a method of operating a performance-enhancedapparatus, comprising rendering a source view associated with a firstdisplay plane in a plurality of display planes, re-projecting therendered source view to a second display plane in the plurality ofdisplay planes to obtain a re-projected view, and filling one or moreholes in the re-projected view based on one or more of extended field ofview data corresponding to the source view, rasterization datacorresponding to the source view or rasterization data corresponding tothe re-projected view.

Example 72 may include the method of Example 71, wherein when the one ormore holes are filled based on the extended field of view data, there-projected view has a non-extended field of view.

Example 73 may include the method of Example 71, wherein when the one ormore holes are filled based on the rasterization data corresponding tothe source view, the method further includes disabling a depth testduring rendering of the source view, and conducting the depth testduring filling of the one or more holes in the re-projected view.

Example 74 may include the method of Example 71, wherein when the one ormore holes are filled based on the rasterization data corresponding tothe re-projected view, the method further includes pre-populating adepth buffer during re-projection of the rendered source view, andconducting a depth test during filling of the one or more holes based ondata in the depth buffer.

Example 75 may include the method of Example 71, further includingdetermining a focus point relative to the plurality of display planes,and varying, on a per display plane basis, a resolution of scene contentpresented on the plurality of display planes based on the focus point.

Example 76 may include the method of Example 75, wherein the methodfurther includes varying, on the per display plane basis, a view densityof the scene content presented on the plurality of display planes basedon the focus point.

Example 77 may include the method of Example 75, wherein the methodfurther includes varying, on the per display plane basis, a view updatefrequency of the scene content presented on the plurality of displayplanes based on the focus point.

Example 78 may include the method of Example 75, wherein the methodfurther includes separating peripheral views into bins having one ormore of different resolutions, different view densities or differentupdate frequencies.

Example 79 may include the method of Example 71, further includingdetermining a set of primitives associated with the plurality of displayplanes, and conducting a hierarchical sequence of culling operations onthe set of primitives.

Example 80 may include the method of Example 79, wherein thehierarchical sequence of culling operations includes a near plane-farplane culling operation that rejects primitives behind a farthestdisplay plane in the plurality of display planes and rejects primitivesin front of a nearest display plane in the plurality of display planes.

Example 81 may include the method of Example 80, wherein thehierarchical sequence of culling operations includes a coarse frustumculling operation that is conducted on a per eye basis and after thenear plane-far plane culling operation, and wherein the coarse frustumculling operation is to reject primitives outside a top frustum plane ofa topmost viewport, a bottom frustum plane of a bottommost viewport, aleft frustum plane of a leftmost viewport and a right frustum plane of arightmost viewport.

Example 82 may include the method of Example 81, wherein thehierarchical sequence of culling operations includes a fine frustumculling operation that is conducted after the coarse frustum cullingoperation, and wherein the logic coupled to the one or more substratesis to populate one or more tile bins with primitives that pass the finefrustum culling operation.

Example 83 may include the method of Example 71, further includingidentifying first image data associated with scene content on a firstdisplay plane in the plurality of display planes, identifying a firstposition change between the scene content on the first display plane andthe scene content on a second display plane in the plurality of displayplanes, and approximating, based on the first image data and the firstposition change, second image data associated with the scene content onthe second display plane.

Example 84 may include the method of Example 83, further includingidentifying a second position change between the scene content on thefirst display plane and the scene content on a third display plane inthe plurality of display planes, and approximating, based on the firstimage data and the second position change, third image data associatedwith the scene content on the third display plane.

Example 85 may include a method of operating a performance-enhancedapparatus, comprising determining a focus point relative to a pluralityof display planes, and varying, on a per display plane basis, aresolution of scene content presented on the plurality of display planesbased on the focus point.

Example 86 may include the method of Example 85, wherein the methodfurther includes varying, on the per display plane basis, a view densityof the scene content presented on the plurality of display planes basedon the focus point.

Example 87 may include the method of Example 85, wherein the methodfurther includes varying, on the per display plane basis, a view updatefrequency of the scene content presented on the plurality of displayplanes based on the focus point.

Example 88 may include the method of Example 85, wherein the methodfurther includes separating peripheral views into bins having one ormore of different resolutions, different view densities or differentupdate frequencies.

Example 89 may include the method of Example 85, further includingdetermining a set of primitives associated with the plurality of displayplanes, and conducting a hierarchical sequence of culling operations onthe set of primitives.

Example 90 may include the method of Example 89, wherein thehierarchical sequence of culling operations includes a near plane-farplane culling operation that rejects primitives behind a farthestdisplay plane in the plurality of display planes and rejects primitivesin front of a nearest display plane in the plurality of display planes.

Example 91 may include the method of Example 90, wherein thehierarchical sequence of culling operations includes a coarse frustumculling operation that is conducted on a per eye basis and after thenear plane-far plane culling operation, and wherein the coarse frustumculling operation is to reject primitives outside a top frustum plane ofa topmost viewport, a bottom frustum plane of a bottommost viewport, aleft frustum plane of a leftmost viewport and a right frustum plane of arightmost viewport.

Example 92 may include the method of Example 91, wherein thehierarchical sequence of culling operations includes a fine frustumculling operation that is conducted after the coarse frustum cullingoperation, and wherein the logic coupled to the one or more substratesis to populate one or more tile bins with primitives that pass the finefrustum culling operation.

Example 93 may include the method of Example 85, further includingidentifying first image data associated with the scene content on afirst display plane in the plurality of display planes, identifying afirst position change between the scene content on the first displayplane and the scene content on a second display plane in the pluralityof display planes, and approximating, based on the first image data andthe first position change, second image data associated with the scenecontent on the second display plane.

Example 94 may include the method of Example 93, further includingidentifying a second position change between the scene content on thefirst display plane and the scene content on a third display plane inthe plurality of display planes, and approximating, based on the firstimage data and the second position change, third image data associatedwith the scene content on the third display plane.

Example 95 may include a method of operating a performance-enhancedapparatus, comprising determining a set of primitives associated with aplurality of display planes, and conducting a hierarchical sequence ofculling operations on the set of primitives.

Example 96 may include the method of Example 95, wherein thehierarchical sequence of culling operations includes a near plane-farplane culling operation that rejects primitives behind a farthestdisplay plane in the plurality of display planes and rejects primitivesin front of a nearest display plane in the plurality of display planes.

Example 97 may include the method of Example 96, wherein thehierarchical sequence of culling operations includes a coarse frustumculling operation that is conducted on a per eye basis and after thenear plane-far plane culling operation, and wherein the coarse frustumculling operation is to reject primitives outside a top frustum plane ofa topmost viewport, a bottom frustum plane of a bottommost viewport, aleft frustum plane of a leftmost viewport and a right frustum plane of arightmost viewport.

Example 98 may include the method of Example 97, wherein thehierarchical sequence of culling operations includes a fine frustumculling operation that is conducted after the coarse frustum cullingoperation, and wherein the logic coupled to the one or more substratesis to populate one or more tile bins with primitives that pass the finefrustum culling operation.

Example 99 may include the method of Example 95, wherein the logiccoupled to the one or more substrates to identifying first image dataassociated with scene content on a first display plane in the pluralityof display planes, identifying a first position change between the scenecontent on the first display plane and the scene content on a seconddisplay plane in the plurality of display planes, and approximating,based on the first image data and the first position change, secondimage data associated with the scene content on the second displayplane.

Example 100 may include the method of Example 98, further includingidentifying a second position change between the scene content on thefirst display plane and the scene content on a third display plane inthe plurality of display planes, and approximating, based on the firstimage data and the second position change, third image data associatedwith the scene content on the third display plane.

Example 101 may include a method of operating a performance-enhancedapparatus, comprising identifying first image data associated with scenecontent on a first display plane in a plurality of display planes,identifying a first position change between the scene content on thefirst display plane and the scene content on a second display plane inthe plurality of display planes, and approximating, based on the firstimage data and the first position change, second image data associatedwith the scene content on the second display plane.

Example 102 may include the method of Example 101, further includingidentifying a second position change between the scene content on thefirst display plane and the scene content on a third display plane inthe plurality of display planes, and approximating, based on the firstimage data and the second position change, third image data associatedwith the scene content on the third display plane.

Example 103 may include a performance-enhanced graphics apparatuscomprising means for performing any one of the methods of Examples 52 to102.

Example 104 may include at least one computer readable storage mediumcomprising a set of instructions, which when executed by a computingsystem, cause the computing system to perform the method of any one ofExamples 52 to 102.

Embodiments are applicable for use with all types of semiconductorintegrated circuit (“IC”) chips. Examples of these IC chips include butare not limited to processors, controllers, chipset components,programmable logic arrays (PLAs), memory chips, network chips, systemson chip (SoCs), SSD/NAND controller ASICs, and the like. In addition, insome of the drawings, signal conductor lines are represented with lines.Some may be different, to indicate more constituent signal paths, have anumber label, to indicate a number of constituent signal paths, and/orhave arrows at one or more ends, to indicate primary information flowdirection. This, however, should not be construed in a limiting manner.Rather, such added detail may be used in connection with one or moreexemplary embodiments to facilitate easier understanding of a circuit.Any represented signal lines, whether or not having additionalinformation, may actually comprise one or more signals that may travelin multiple directions and may be implemented with any suitable type ofsignal scheme, e.g., digital or analog lines implemented withdifferential pairs, optical fiber lines, and/or single-ended lines.

The term “coupled” may be used herein to refer to any type ofrelationship, direct or indirect, between the components in question,and may apply to electrical, mechanical, fluid, optical,electromagnetic, electromechanical or other connections. In addition,the terms “first”, “second”, etc. may be used herein only to facilitatediscussion, and carry no particular temporal or chronologicalsignificance unless otherwise indicated. Additionally, it is understoodthat the indefinite articles “a” or “an” carries the meaning of “one ormore” or “at least one”.

As used in this application and in the claims, a list of items joined bythe term “one or more of” may mean any combination of the listed terms.For example, the phrases “one or more of A, B or C” may mean A, B, C; Aand B; A and C; B and C; or A, B and C.

The embodiments have been described above with reference to specificembodiments. Persons skilled in the art, however, will understand thatvarious modifications and changes may be made thereto without departingfrom the broader spirit and scope of the embodiments as set forth in theappended claims. The foregoing description and drawings are,accordingly, to be regarded in an illustrative rather than a restrictivesense.

1. (canceled)
 2. A computing system comprising: a graphics processor; acentral processing unit; and a memory including a set of instructions,which when executed by one or more of the graphics processor or thecentral processing unit, cause the computing system to: determine afirst plurality of primitives associated with a scene; reject a firstprimitive from the first plurality of primitives that are behind a firstdisplay plane to generate a second plurality of primitives; and reject asecond primitive that is in front of a second display plane to generatethe second plurality of primitives.
 3. The system of claim 2, whereinthe first display plane is a display plane that is farthest from a user,and the second display plane is a display plane that is closest to theuser.
 4. The system of claim 2, wherein the instructions, when executed,cause the computing system to: execute, on a per eye basis, a coarsefrustum culling operation on the second plurality of primitives.
 5. Thesystem of claim 2, wherein the instructions, when executed, cause thecomputing system to: determine a left frustum plane for a left viewportassociated with a left eye of a user; determine a right frustum planefor a right viewport associated with a right eye of the user; determinea top frustum plane of a top viewport; determine a bottom frustum planeof a bottom viewport; and reject a third primitive of the secondplurality of primitives based on the top frustum plane, the bottomfrustum plane, the left frustum plane and the right frustum plane togenerate a third plurality of primitives.
 6. The system of claim 5,wherein the instructions, when executed, cause the computing system to:execute fine frustum culling operations to assign the third plurality ofprimitives to one or more of left tile bins associated with a left eyeof the user or right tile bins associated with a right eye of the user.7. The system of claim 2, wherein the instructions, when executed, causethe computing system to: reject a third primitive of the secondplurality of primitives based on distances between vertices of the thirdprimitive and each of a top frustum plane, a bottom frustum plane, aleft frustum plane and a right frustum plane.
 8. An apparatuscomprising: one or more substrates; and logic coupled to the one or moresubstrates, wherein the logic is implemented in one or more ofconfigurable logic or fixed-functionality logic hardware, the logiccoupled to the one or more substrates to: determine a first plurality ofprimitives associated with a plurality of display planes; reject a firstprimitive from the first plurality of primitives that are behind a firstdisplay plane to generate a second plurality of primitives; and reject asecond primitive that is in front of a second display plane to generatethe second plurality of primitives.
 9. The apparatus of claim 8, whereinthe first display plane is a display plane that is farthest from a user,and the second display plane is a display plane that is closest to theuser.
 10. The apparatus of claim 8, wherein the logic coupled to the oneor more substrates is to: execute, on a per eye basis, a coarse frustumculling operation on the second plurality of primitives.
 11. Theapparatus of claim 10, wherein the logic coupled to the one or moresubstrates is to: determine a left frustum plane for a left viewportassociated with a left eye of a user; determine a right frustum planefor a right viewport associated with a right eye of the user; determinea top frustum plane of a top viewport; determine a bottom frustum planeof a bottom viewport; and reject a third primitive of the secondplurality of primitives based on the top frustum plane, the bottomfrustum plane, the left frustum plane and the right frustum plane togenerate a third plurality of primitives.
 12. The apparatus of claim 11,wherein the logic coupled to the one or more substrates is to: executefine frustum culling operations to assign the third plurality ofprimitives to one or more of left tile bins associated with a left eyeof the user or right tile bins associated with a right eye of the user.13. The apparatus of claim 8, wherein the logic coupled to the one ormore substrates is to: reject a third primitive of the second pluralityof primitives based on distances between vertices of the third primitiveand each of a top frustum plane, a bottom frustum plane, a left frustumplane and a right frustum plane.
 14. At least one computer readablestorage medium comprising a set of instructions, which when executed bya computing device, cause the computing device to: determine a firstplurality of primitives associated with a scene; reject a firstprimitive from the first plurality of primitives that are behind a firstdisplay plane to generate a second plurality of primitives; and reject asecond primitive that is in front of a second display plane to generatethe second plurality of primitives.
 15. The at least one computerreadable storage medium of claim 14, wherein the first display plane isa display plane that is farthest from a user, and the second displayplane is a display plane that is closest to the user.
 16. The at leastone computer readable storage medium of claim 14, wherein theinstructions, when executed, cause the computing device to: execute, ona per eye basis, a coarse frustum culling operation on the secondplurality of primitives.
 17. The at least one computer readable storagemedium of claim 14, wherein the instructions, when executed, cause thecomputing device to: determine a left frustum plane for a left viewportassociated with a left eye of a user; determine a right frustum planefor a right viewport associated with a right eye of the user; determinea top frustum plane of a top viewport; determine a bottom frustum planeof a bottom viewport; and reject a third primitive of the secondplurality of primitives based on the top frustum plane, the bottomfrustum plane, the left frustum plane and the right frustum plane togenerate a third plurality of primitives.
 18. The at least one computerreadable storage medium of claim 17, wherein the instructions, whenexecuted, cause the computing device to execute fine frustum cullingoperations to assign the third plurality of primitives to one or more ofleft tile bins associated with a left eye of the user or right tile binsassociated with a right eye of the user.
 19. The at least one computerreadable storage medium of claim 14, wherein the instructions, whenexecuted, cause the computing device: reject a third primitive of thesecond plurality of primitives based on distances between vertices ofthe third primitive and each of a top frustum plane, a bottom frustumplane, a left frustum plane and a right frustum plane.
 20. A methodcomprising: determining a first plurality of primitives associated witha scene; rejecting a first primitive from the first plurality ofprimitives that are behind a first display plane to generate a secondplurality of primitives; and rejecting a second primitive that is infront of a second display plane to generate the second plurality ofprimitives.
 21. The method of claim 20, wherein the first display planeis a display plane that is farthest from a user, and the second displayplane is a display plane that is closest to the user.
 22. The method ofclaim 20, further comprising: executing, on a per eye basis, a coarsefrustum culling operation on the second plurality of primitives.
 23. Themethod of claim 20, further comprising: determining a left frustum planefor a left viewport associated with a left eye of a user; determining aright frustum plane for a right viewport associated with a right eye ofthe user; determining a top frustum plane of a top viewport; determininga bottom frustum plane of a bottom viewport; and rejecting a thirdprimitive of the second plurality of primitives based on the top frustumplane, the bottom frustum plane, the left frustum plane and the rightfrustum plane to generate a third plurality of primitives.
 24. Themethod of claim 23, further comprising executing fine frustum cullingoperations to assign the third plurality of primitives to one or more ofleft tile bins associated with a left eye of the user or right tile binsassociated with a right eye of the user.
 25. The method of claim 20,further comprising: rejecting a third primitive of the second pluralityof primitives based on distances between vertices of the third primitiveand each of a top frustum plane, a bottom frustum plane, a left frustumplane and a right frustum plane.